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Journal articles on the topic 'AI Telemedicine'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Kilari, Sai Dhiresh. "AI In Telemedicine." International Journal of Scientific Research and Management (IJSRM) 11, no. 04 (2023): 851–54. https://doi.org/10.18535/ijsrm/v11i04.mp3.

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Telemedicine has potentially witnessed a notable growth during the recent years, specifically driven by technical advancements, a globalised impact that Covid-19 pandemic had as well as evolution in the healthcare needs [1]. Telemedicine powered by AI necessarily integrates the likes of Machine Learning (ML), computer vision as well as Natural Language Processing (NLP) in order to bring notable improvement to the patient care by allowing remote forms of diagnostics, personalized treatment plans as well as predictive analytics. This paper mainly highlights the role of AI in the field of Telemed

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Ejike Innocent Nwankwo, Ebube Victor Emeihe, Mojeed Dayo Ajegbile, Janet Aderonke Olaboye, and Chukwudi Cosmos Maha. "Integrating Telemedicine and AI to Improve Healthcare Access in Rural Settings." International Journal of Life Science Research Archive 7, no. 1 (2024): 059–77. http://dx.doi.org/10.53771/ijlsra.2024.7.1.0061.

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Integrating telemedicine and artificial intelligence (AI) presents a promising solution to enhance healthcare access and quality in rural settings, where limited medical resources and geographical barriers pose significant challenges. This paper explores the synergistic potential of telemedicine and AI technologies in bridging healthcare disparities in rural areas. Telemedicine enables remote consultations, diagnosis, and treatment by leveraging telecommunications technology, significantly expanding healthcare access to underserved populations. AI enhances telemedicine's capabilities by provid

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Raihan, Kevin, and Sinta Dewi Rosadi. "Have AI-Enhanced Telemedicines in Indonesia Adopted the Principles of Personal Data Protection?" Yustisia Jurnal Hukum 13, no. 2 (2024): 151. http://dx.doi.org/10.20961/yustisia.v13i2.85996.

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<em>Artificial Intelligence (AI)-enhanced telemedicines pertains to legal problems especially on the protection of personal data considering the its nature. However, there has not been any research specifically examining the protection of personal data in in Indonesia with the perspective of Law Number 27 of 2022 regarding Personal Data Protection (PDP Law), specifically regarding the analysis of personal data protection principles (PDP Principles). Therefore, this research aimed to evaluate and analyze the practice of telemedicines in Indonesia on the adoption of PDP Principles from the

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Perez, Kinalyne, Daniela Wisniewski, Arzu Ari, Kim Lee, Cristian Lieneck, and Zo Ramamonjiarivelo. "Investigation into Application of AI and Telemedicine in Rural Communities: A Systematic Literature Review." Healthcare 13, no. 3 (2025): 324. https://doi.org/10.3390/healthcare13030324.

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Recent advances in artificial intelligence (AI) and telemedicine are transforming healthcare delivery, particularly in rural and underserved communities. Background/Objectives: The purpose of this systematic review is to explore the use of AI-driven diagnostic tools and telemedicine platforms to identify underlying themes (constructs) in the literature across multiple research studies. Method: The research team conducted an extensive review of studies and articles using multiple research databases that aimed to identify consistent themes and patterns across the literature. Results: Five underl

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Toritsemogba Tosanbami Omaghomi, Oluwafunmi Adijat Elufioye, Opeoluwa Akomolafe, Evangel Chinyere Anyanwu, and Ifeoma Pamela Odilibe. "A COMPREHENSIVE REVIEW OF TELEMEDICINE TECHNOLOGIES: PAST, PRESENT, AND FUTURE PROSPECTS." International Medical Science Research Journal 4, no. 2 (2024): 183–93. http://dx.doi.org/10.51594/imsrj.v4i2.811.

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This comprehensive review explores telemedicine technologies' past, present, and future. Telemedicine has evolved significantly, providing healthcare services and exchanging medical information remotely. The historical overview traces its roots from early experiments to its current state, marked by advanced technology, diverse applications, and increased adoption, especially during the COVID-19 pandemic. Emerging technologies like AI, VR, IoT, and blockchain promise to revolutionize telemedicine, enhancing diagnostics, patient monitoring, and personalized treatment. Potential applications rang

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Kayusi, Fredrick, Srinivas Kasulla, S. J. Malik, et al. "Evaluating Patient Rights and Agency: An In-depth Examination of Autonomous Decision-Making in AI-Powered Telemedicine." Health & Pharmaceutical Research 2024, no. 11 (2024): 1–11. https://doi.org/10.62839/HPR.v01.v01.1-11.

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<strong>Abstract:</strong> This study examines the adequacy of regulations concerning consent and patient autonomy in AI telemedicine in Ghana. Using the IRAC (Issue, Rule, Analysis, and Conclusion) method, the research analyzes existing Ghanaian healthcare laws and regulations in the context of AI-driven telemedicine. The study finds significant gaps in the current regulatory framework, including a lack of specific provisions for informed consent in AI telemedicine, unclear guidelines on maintaining patient autonomy, and inadequate addressing of liability issues in AI-assisted healthcare. Rec

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Kooptiwoot, Suwimon, Chaisri Tharasawatpipat, Sivapan Choo-In, Pantip Kayee, and Bagher Javadi. "AI-driven telemedicine: Optimizing daily dietary recommendations amidst the COVID-19 pandemic." Journal of Infrastructure, Policy and Development 8, no. 11 (2024): 8908. http://dx.doi.org/10.24294/jipd.v8i11.8908.

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Amidst the COVID-19 pandemic, the imperative of physical distancing has underscored the necessity for telemedicine solutions. Traditionally, telemedicine systems have operated synchronously, requiring scheduled appointments. This study introduces an innovative telemedicine system integrating Artificial Intelligence (AI) to enable asynchronous communication between physicians and patients, eliminating the need for appointments and providing round-the-clock access from any location. The AI-Telemedicine system was developed utilizing Google Sheets and Google Forms. Patients can receive dietary re

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Adeyoyin, Adebisi. "Telemedicine and AI in Remote Patient Monitoring." Researchgate 3513, no. 19 (2024): 34. https://doi.org/10.5281/zenodo.11183975.

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The integration of Telemedicine and Artificial Intelligence (AI) in Remote Patient Monitoring (RPM) represents a transformative shift in healthcare delivery. Telemedicine enables remote access to healthcare services, while AI enhances data analytics and decision-making capabilities. This abstract explores the significance of Telemedicine and AI in RPM, highlighting their roles, advantages, challenges, and future implications. Telemedicine facilitates remote monitoring of patients' vital signs and symptoms, improving accessibility and enabling timely interventions. AI in RPM provides real-time

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Onetiu, Florina, Melania Lavinia Bratu, Roxana Folescu, Felix Bratosin, and Tiberiu Bratu. "Assessing Medical Students’ Perceptions of AI-Integrated Telemedicine: A Cross-Sectional Study in Romania." Healthcare 13, no. 9 (2025): 990. https://doi.org/10.3390/healthcare13090990.

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Background and Objectives: The rapid advancement of Artificial Intelligence (AI) has driven the expansion of telemedicine solutions worldwide, enabling remote diagnosis, patient monitoring, and treatment support. This study aimed to explore medical students’ perceptions of AI in telemedicine, focusing on how these future physicians view AI’s potential, benefits, and challenges. Methods: A cross-sectional survey was conducted among 161 Romanian medical students spanning Years 1 through 6. Participants completed a 15-item questionnaire covering demographic factors, prior exposure to AI, attitude

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Patel, Princal. "Role of Artificial Intelligence in Telemedicine." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (2023): 443–49. http://dx.doi.org/10.22214/ijraset.2023.55211.

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Abstract: This article presents an overview of artificial intelligence's (AI) function in telemedicine, emphasising how revolutionary it has the potential to be. The use of AI in telemedicine improves patient experiences, allows for faster and more accurate diagnosis, and lessens the need for in-person visits. The background, classifications, advantages, and disadvantages of telemedicine are examined. In-depth analysis of how AI is reshaping telemedicine is provided in the paper, including how it affects accurate diagnosis, patient monitoring, geriatric care, hospital visits, and physician wea

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Hwang, Sewoong, Yungyeong Song, and Jonghyuk Kim. "Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application." Applied Sciences 11, no. 6 (2021): 2707. http://dx.doi.org/10.3390/app11062707.

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This study indirectly verifies the possibility of telemedicine for humans through a mobile application (app) targeting pets. It examined the perception of telemedicine services and the current status of the companion animal industry, the app platform, and its applied technology by industry domain, and four representative types of artificial intelligence (AI) technologies applicable in the medical field. A survey was conducted through an app implementing pet telemedicine, and hypotheses were established and statistically tested based on the adoption period of pets, health status, mobile service

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J Dr. Uma Devi A, Naveen Raj K, Mugilan M, Supriya Latha Ananthan, Neha S N, and Sutharsan T. "AI in Healthcare." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 04 (2025): 1100–1111. https://doi.org/10.47392/irjaem.2025.0180.

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Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostics, treatment planning, and patient care. This article provides an overview of the use of AI in healthcare by means of Electronic Health Records (EHRs), AI symptom checkers, drug discovery, predictive health analysis, and telemedicine. AI has significantly increased efficiency, reduced medical errors, and offered personalized treatments. But present AI-enabled healthcare systems lack some features such as the lack of physical examination, cybersecurity, poor internet connectivity, and medical miscommunication via

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Ikhalea, Nura, Ernest Chinonso Chianumba, Ashiata Yetunde Mustapha, Adelaide Yeboah Forkuo, and Damilola Osamika. "A Model for Strengthening Health Systems in Low-Resource Settings Using AI and Telemedicine." International Journal of Future Engineering Innovations 1, no. 1 (2024): 86–92. https://doi.org/10.54660/ijfei.2024.1.1.86-92.

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This paper explores the integration of artificial intelligence (AI) and telemedicine as a transformative solution for strengthening healthcare systems in low-resource settings. It examines how AI-driven technologies, including diagnostic support, treatment planning, and patient monitoring, can enhance telemedicine platforms to provide accessible, efficient, and personalized healthcare. The synergy between AI and telemedicine is explored through case studies and global best practices, demonstrating their combined potential to address healthcare challenges in rural and underserved regions. The p

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Mohanadas, Sadhasivam. "Intelligent Horizons: Navigating the Benefits and Boundaries of AI-Driven Telemedicine." European Journal of Computer Science and Information Technology 13, no. 3 (2025): 43–65. https://doi.org/10.37745/ejcsit.2013/vol13n34365.

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Telemedicine and artificial intelligence (AI) integration has revolutionized the healthcare system through accurate diagnosis, effective treatment, and remote consultations. Some of the technologies used in AI include machine learning algorithms and natural language processing technology, which help algorithms offer predictive analytics and personalized care. In addition, these technologies have reduced the clinical staff's work burden and have led to increased patient engagement. However, despite these skyrocketing forward movements, AI-driven telemedicine faces challenges such as data privac

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Wang, Yufeng, Qi Liu, and Rui Zhang. "How the Healthy China 2030 Policy Promotes the Construction of a Rural Telemedicine Chronic Disease Management Service System." Studies in Social Science & Humanities 4, no. 2 (2025): 37–45. https://doi.org/10.56397/sssh.2025.03.06.

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The Healthy China 2030 policy aims to enhance healthcare accessibility and equity, with a strong emphasis on integrating telemedicine into rural chronic disease management. With China’s rapidly aging population and a high prevalence of chronic diseases such as hypertension, diabetes, and cardiovascular conditions, rural healthcare systems face significant challenges due to limited medical infrastructure, specialist shortages, and financial barriers. Telemedicine has emerged as a critical solution, enabling remote consultations, AI-assisted diagnostics, and digital health monitoring to improve

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Mridusmita, Barman, and Bhat Sanjana. "Assessing Healthcare Professionals’ Knowledge and Awareness of Artificial Intelligence-Based Telemedicine for Enhancing Remote Diagnosis: A Systematic Review." Journal Global Value XVI, SI (2025): 101–8. https://doi.org/10.31995/jgv.2025.v16isi7.015.

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The incorporation of Artificial Intelligence (AI) in telemedicine has revolutionized remote diagnosis, enhancing the accessibility and quality of healthcare. This systematic review sought to evaluate healthcare professionals’ (HCPs) awareness and knowledge of AI-based telemedicine, and factors that contributed to its uptake and use. A thorough literature search was undertaken, and studies were chosen based on predetermined criteria. The review highlights the current gaps in HCPs’ awareness and knowledge to look after how these would guide future training and education to ensure the optimal app

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Amjad, Ayesha, Piotr Kordel, and Gabriela Fernandes. "A Review on Innovation in Healthcare Sector (Telehealth) through Artificial Intelligence." Sustainability 15, no. 8 (2023): 6655. http://dx.doi.org/10.3390/su15086655.

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Artificial intelligence (AI) has entered the mainstream as computing power has improved. The healthcare industry is undergoing dramatic transformations at present. One of the most recent industries to heavily use AI is telehealth, which is used for anything from issuing electronic healthcare cards to providing individual counselling. Artificial intelligence (AI) is influencing telehealth in the United States in a major way. Using AI in telehealth to allow clinicians to make real-time, data-driven rich choices is critical to offering a better patient experience and improved health outcomes as p

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Malay Sarkar, Raktim Dey, and Md Tuhin Mia. "Artificial Intelligence in telemedicine and remote patient monitoring: Enhancing virtual healthcare through AI-driven diagnostic and predictive technologies." International Journal of Science and Research Archive 15, no. 2 (2025): 1046–55. https://doi.org/10.30574/ijsra.2025.15.2.1402.

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The integration of Artificial Intelligence (AI) in telemedicine and remote patient monitoring has significantly transformed modern healthcare by enhancing accessibility, efficiency, and diagnostic precision. AI-powered technologies, including machine learning algorithms, predictive analytics, and natural language processing, have facilitated real-time health monitoring, early disease detection, and personalized treatment recommendations. The incorporation of AI-driven chatbot and virtual assistants has streamlined remote consultations, enabling healthcare professionals to manage patient inquir

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Goutham, Bilakanti. "The Impact of Telemedicine on Patient Care and Accessibility." International Journal of Leading Research Publication 4, no. 2 (2023): 1–12. https://doi.org/10.5281/zenodo.15196894.

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The Telemedicine has proven to be an innovative force of healthcare, far enhancing access to medical care in rural and medically underserved populations. This work addresses how telemedicine can extend healthcare access to bridge gaps in healthcare, optimize patient outcomes, and optimize use of resources. It addresses benefits of telemedicine, such as increased accessibility, cost savings, and improved patient engagement. Also, the study goes into its vulnerability, such as technical limitations, bureaucratic resistance, and issues on data privacy and security. In addition, the paper sees the

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M., Harini. "Telemedicine and Health Care Accessibility: AI-Powered Remote Diagnostics." Siddhanta's International Journal of Advanced Research in Arts & Humanities 1, no. 5 (2024): 34–41. https://doi.org/10.5281/zenodo.11611305.

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Telemedicine, augmented by AI-powered remote diagnostics, is transforming healthcare accessibility by bridging geographical, economic, and logistical gaps. This integration facilitates early disease detection, continuous health monitoring, and personalized care, significantly improving patient outcomes and reducing healthcare costs. AI’s capabilities in analyzing medical data and providing decision support enhance diagnostic accuracy and treatment effectiveness. Additionally, telemedicine expands specialist access and addresses workforce shortages, particularly in underserved regions. De

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Harini, M. "Telemedicine and health care accessibility: AI-powered remote Diagnostics." Bulletin of Nexus 1, no. 1 (2024): 1–5. https://doi.org/10.5281/zenodo.14538611.

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<em>Telemedicine, augmented by AI-powered remote diagnostics, is transforming healthcare accessibility by bridging geographical, economic, and logistical gaps. This integration facilitates early disease detection, continuous health monitoring, and personalized care, significantly improving patient outcomes and reducing healthcare costs. AI’s capabilities in analyzing medical data and providing decision support enhance diagnostic accuracy and treatment effectiveness. Additionally, telemedicine expands specialist access and addresses workforce shortages, particularly in underserved regions

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Alqahtany, Amjad Saud, ‏Salma Ali Khrami, ‏Abdulaziz Shaem Alsharari, et al. "Advancements in telemedicine: Transforming healthcare delivery and enhancing access for providers and patients alike." International journal of health sciences 6, S10 (2022): 1771–85. http://dx.doi.org/10.53730/ijhs.v6ns10.15103.

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Background: The advent of telemedicine marks a significant transformation in healthcare delivery, leveraging technology to improve accessibility and efficiency for both providers and patients. From early methods of distant communication to modern innovations like telehealth and mobile health, telemedicine has evolved alongside technological advancements. Aim: This article explores the historical development, current applications, and future potential of telemedicine, emphasizing its role in enhancing healthcare delivery and access. Methods: The article reviews the evolution of telemedicine, be

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Zama, Daniele, Andrea Borghesi, Alice Ranieri, et al. "Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology." Children 11, no. 11 (2024): 1401. http://dx.doi.org/10.3390/children11111401.

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Background: Pediatric dermatology represents one of the most underserved subspecialties in pediatrics. Artificial intelligence (AI) and telemedicine have become considerable in dermatology, reaching diagnostic accuracy comparable to or exceeding that of in-person visits. This work aims to review the current state of telemedicine and AI in pediatric dermatology, suggesting potential ways to address existing issues and challenges. Methods: We conducted a literature review including only articles published in the last 15 years. A total of 458 studies were identified, of which only 76 were include

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Abbasi, Nasrullah. "Artificial Intelligence in Remote Monitoring and Telemedicine." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 1, no. 1 (2024): 258–72. http://dx.doi.org/10.60087/jaigs.v1i1.202.

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Telemedicine, remote monitoring coupled with Artificial Intelligence innovations are redesigning the face of the healthcare sector in record way and increasing satisfaction levels for patients’ clinical enhancements, reduced charges and increased effectiveness in the delivery of services. The applied and advanced AI technologies consist of machine learning, natural language processing, and predictive analytics used in applications for RPM, PT, and VC. In RPM, AI augments the processes of data aggregation and data analysis of patients’ real-time health data from wearable and other digital healt

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Penner, Regina. "Telemedicine and Diagnostic Artificial Intelligence: Evolution, Prospects, and Social Challenges." Argumentos de Razón Técnica, no. 27 (2024): 215–30. https://doi.org/10.12795/argumentos/2024.i27.07.

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This article examines the evolution of telemedicine as one of the key fields in modern medicine, utilizing information and communication technologies to provide medical services remotely. The study’s goal is to analyze the historical development of telemedicine and its impact on medical practice, as well as assess the prospects of using Diagnostic Artificial Intelligence (Diagnostic AI) in telemedicine. The research methodology includes discourse analysis, based on the works of Michel Foucault and Gilles Deleuze, allowing the examination of medical institutions as mechanisms for controlling an

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Dr. Rohith Vangalla. "AI Integration in Telemedicine: Revolutionizing Virtual Healthcare Delivery." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1858–66. https://doi.org/10.32628/cseit241061228.

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This comprehensive article explores the transformative impact of Artificial Intelligence integration in telemedicine services, highlighting its pivotal role in revolutionizing virtual healthcare delivery. The article examines various dimensions of AI applications in healthcare, including real-time data analysis, remote patient monitoring systems, patient engagement platforms, operational efficiency improvements, clinical benefits, and future developments. The article reveals significant advancements in diagnostic accuracy, patient care personalization, and healthcare accessibility through AI-p

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Minal, Khandare, J. Sahana, S. Shivani, S. Kumar Sneha, and R. Rakshitha. "Rural Healthcare Empowerment: AI Enabled Telemedicine KIOSK." Recent Trends in Computer Graphics and Multimedia Technology 6, no. 2 (2024): 1–9. https://doi.org/10.5281/zenodo.11024382.

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<em>Access to healthcare services in rural areas has long been a challenge, with limited resources and healthcare facilities often leaving residents underserved. The advent of telemedicine has brought about a promising solution, bridging the gap be- tween rural communities and healthcare providers. This Project presents a novel approach to enhancing telemedicine services in rural areas through the deployment of AI-powered Telemedicine Kiosks. These kiosks are designed to provide convenient and com- prehensive healthcare access to remote communities, empowering patients to receive timely medica

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Talati, Dhruvitkumar. "Telemedicine and AI in Remote Patient Monitoring." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 3 (2023): 254–55. http://dx.doi.org/10.60087/jklst.vol2.n3.p255.

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This article explores how telemedicine, especially with the help of artificial intelligence (AI), is transforming healthcare. It covers its applications in monitoring patients, managing chronic diseases like diabetes, and improving cardiovascular care. The importance of wearable devices and non-invasive blood glucose monitoring is highlighted. The article emphasizes how AI-driven remote patient monitoring can enhance healthcare by providing early intervention, reducing hospitalizations, and offering personalized care

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C, Manohar. "AI-Assisted Telemedicine Kiosk for Rural India." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem49184.

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ABSTRACT: The COVID-19 pandemic highlighted the necessity for intelligent and scalable telehealth platforms. RemedyAI is an AI-powered web-based telemedicine platform that allows patients to virtually consult with medical professionals, gain access to smart symptom analysis, and schedule appointments and keep medical records. This paper introduces the architecture, design, and implementation of RemedyAI using a new web stack and augmented with AI algorithms for initial diagnosis and triage. The system is based on modular elements, real-time communication standards, and an easy-to-use interface

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Sebastian, Rommy. "The Role of Artificial Intelligence in Telemedicine: Legal Considerations under Indonesian Health Laws." Devotion : Journal of Research and Community Service 5, no. 12 (2024): 1558–68. https://doi.org/10.59188/devotion.v5i12.20694.

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The integration of Artificial Intelligence (AI) in Indonesia’s healthcare system, particularly in telemedicine, presents both opportunities and challenges. AI enhances healthcare delivery by improving diagnostics and patient management, especially in underserved areas. However, its adoption raises legal concerns, particularly around data privacy, security, and professional accountability. Indonesia's regulatory framework, including the Personal Data Protection Law (UU PDP) and Health Ministerial regulations, governs healthcare and data use but has not fully adapted to the complexities of AI. T

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Klang, Eyal, Shelly Soffer, Abraham Tsur, Eyal Shachar, and Adi Lahat. "Innovation in Gastroenterology—Can We Do Better?" Biomimetics 7, no. 1 (2022): 33. http://dx.doi.org/10.3390/biomimetics7010033.

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The health system can reap significant benefits by adopting and implementing innovative measures, as was recently demonstrated and emphasized during the COVID-19 pandemic. Herein, we present our bird’s eye view of gastroenterology’s innovative technologies via utilizing a text-mining technique. We analyzed five research fields that comply with innovation: artificial intelligence (AI), virtual reality (VR), telemedicine, the microbiome, and advanced endoscopy. According to gastroenterology literature, the two most innovative fields were the microbiome and advanced endoscopy. Though artificial i

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B S, Jothi Prakash. "AI-Driven Telemedicine: Bridging Healthcare and Technology for the Future." International Journal for Research in Applied Science and Engineering Technology 13, no. 1 (2025): 557–63. https://doi.org/10.22214/ijraset.2025.66171.

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Telemedicine and Artificial Intelligence (AI) are breaking through the established barriers of healthcare delivery systems all over the world. This paper studies the multiple ways in which AI can make remote healthcare delivery faster, more personalized, and more accessible, such as developing better diagnostics and personalized treatment pathways. Contrary to simply being about automation, telemedicine reminds one that AI keeps changing by data from patients. The new architecture of AI, its cases of disruption, and the future forecast have also been included in the paper. It has also discusse

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Varjushin, M. S. "Legal framework for artificial intelligence technologies in telemedicine." Russian Journal of Telemedicine and E-Health 7, no. 2 (2021): 18–22. http://dx.doi.org/10.29188/2712-9217-2021-7-2-18-22.

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Regulation of artificial intelligence (AI) technologies in healthcare are rapidly developing. Currently, medical organizations faced with the use of AI in conditions of insufficient legislation. There is an analysis of the AI’s legal aspects in the frame of distant interaction of doctors each other and with patients via telemedicine. Special recommendations for introducing and applying AI technologies in different modes given for medical organizations managers. The issue of civil liability for harm caused during the provision of medical care using AI technologies analyzed in detail.

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Alkaabi, Azza, and Deena Elsori. "Navigating digital frontiers in UAE healthcare: A qualitative exploration of healthcare professionals’ and patients’ experiences with AI and telemedicine." PLOS Digital Health 4, no. 4 (2025): e0000586. https://doi.org/10.1371/journal.pdig.0000586.

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The integration of artificial intelligence (AI) and telemedicine into healthcare has significantly advanced patient-centered care, enhancing accessibility, convenience, and patient-doctor relationships. However, different factors determine the extent to which such benefits are realized, especially in unique healthcare settings such as the United Arab Emirates (UAE). In this regard, this research explores healthcare professionals’ and patients’ perspectives to understand various factors that influence the adoption and use of AI in the UAE’s healthcare sector. This research sought to understand

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Lin, Senlin, Yingyan Ma, Yi Xu, et al. "Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data." JMIR Public Health and Surveillance 9 (February 23, 2023): e41624. http://dx.doi.org/10.2196/41624.

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Background Community-based telemedicine screening for diabetic retinopathy (DR) has been highly recommended worldwide. However, evidence from low- and middle-income countries (LMICs) on the choice between artificial intelligence (AI)–based and manual grading–based telemedicine screening is inadequate for policy making. Objective The aim of this study was to test whether the AI model is more worthwhile than manual grading in community-based telemedicine screening for DR in the context of labor costs in urban China. Methods We conducted cost-effectiveness and cost-utility analyses by using decis

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Mustikawati, Irma Finurina, Siti Mahmudah, Lia Fitriyanti, Yuliana Yuliana, and Ressa Andriyani Utami. "The Impact of Telemedicine Adoption, AI Diagnostics, and Patient Data Privacy on Healthcare Accessibility and Quality in 2024." Global International Journal of Innovative Research 2, no. 7 (2024): 1675–85. http://dx.doi.org/10.59613/global.v2i7.237.

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This study explores the impact of telemedicine adoption, AI diagnostics, and patient data privacy on healthcare accessibility and quality in 2024. Employing a qualitative literature review method, this research synthesizes findings from various sources, including academic journals, industry reports, and policy documents, to provide a comprehensive overview of the current state and future implications of these technologies in healthcare. The literature reveals that telemedicine significantly enhances healthcare accessibility by reducing geographical barriers and offering more flexible care opti

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Nguyen, Quoc-Toan. "Advancing Early Alzheimer's Disease Detection in Underdeveloped Areas with Fair Explainable AI Methods." Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, no. 2 (2025): 47–49. https://doi.org/10.1609/aies.v7i2.31907.

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Artificial intelligence (AI)-based telemedicine systems for early Alzheimer's detection using low-cost modalities are vital for rural or underdeveloped areas where travelling distance and high-cost devices like MRI are drawbacks. These systems require eXplainable AI (XAI) for reliable outcomes and intuitive explanations. Current XAI evaluations lack input from medical professionals and overlook stakeholder diversity, leading to potential biases. This project aims to develop a cost-effective AI telemedicine system, enhance early AD detection in underdeveloped areas, reduce healthcare disparitie

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N, Meghana. "Lifelink Medical Emergency Handling App." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40770.

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This paper presents LifeLink, a novel system designed to address the critical challenges of medical emergency response in India. The system integrates advanced technologies such as GPS tracking, AI-powered risk assessment, and telemedicine to streamline emergency response, reduce response times, and improve healthcare outcomes. LifeLink aims to enhance coordination among different entities involved in emergency response, improve access to timely medical care, and ultimately save lives. Key Words: Medical Emergency, Telemedicine, AI, GPS Tracking, Mobile App, IoT

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Deepa, Mogilivaripalli Kurapathi. "Telemedicine for Chronic Disease Management: Evaluating Efficacy in Diverse Patient Populations." Sarcouncil journal of Medical Sciences 4, no. 3 (2025): 107–18. https://doi.org/10.5281/zenodo.15337890.

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Telemedicine has revolutionized chronic disease management by improving accessibility, reducing healthcare costs, and enhancing patient outcomes. The integration of artificial intelligence (AI), the Internet of Things (IoT), cloud computing, and real-time remote patient monitoring has enabled significant advancements in telehealth interventions. This paper explores the efficacy of telemedicine in managing diabetes, cardiovascular diseases, respiratory disorders, hypertension, and mental health conditions while evaluating its impact on diverse populations. A comparative analysis between telemed

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Dr. Zorkóczy, Miklós. "AI Vision #2 – Medical Law And Artificial Intelligence In The Future Of Healthcare." Mesterséges intelligencia 3, no. 2 (2021): 9–18. http://dx.doi.org/10.35406/mi.2021.2.9.

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After having a ride in AI vision # 1 (Zorkóczy, 2021a) when an AI investment was to start up a telemedicine project, this article is about asking questions of the opportunities and problems of AI development in the far future.

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Hudiono, Rini Kartika, and Sri Watini. "Remote Medical Applications of Artificial Intelligence." International Transactions on Artificial Intelligence (ITALIC) 1, no. 2 (2023): 182–87. http://dx.doi.org/10.33050/italic.v1i2.292.

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Artificial intelligence, usually referred to as AI, is one of thetechnologies that is a cornerstone for the sustainability ofhuman activities. When we hear the term AI, we instantly seerobots that can perform tasks independently much like aperson. An artificial intelligence (AI) system might be used toforetell user interests. What role does artificial intelligence (AI) playin the usage of telemedicine, for instance, in the context of mobileapplications? Benefits for the patient will be provided through theapplication of AI technology. Definition of mobile telemedicine as itrelates to Halodoc r

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Karim, Mahit Kumaris, Rajesh Sharma, and Vikram Singh. "The Role of AI-Powered Chatbots in Telemedicine: Improving Accessibility and Patient Engagement." International Journal of Technology and Modeling 2, no. 1 (2023): 1–12. https://doi.org/10.63876/ijtm.v2i1.108.

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The integration of Artificial Intelligence (AI) in telemedicine has significantly transformed healthcare accessibility and patient engagement. AI-powered chatbots serve as virtual assistants, providing real-time medical guidance, symptom assessment, and appointment scheduling, thereby reducing the burden on healthcare professionals and improving patient experiences. This paper explores the role of AI-driven chatbots in enhancing telemedicine services by analyzing their capabilities in symptom triage, personalized health recommendations, and patient communication. Furthermore, we discuss the ad

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Mohameed Aleidhi, Khalid, and Essam Moktar M. Bakr. "Integrating Telemedicine and AI in Paramedic Services: A Systematic Review of Innovations in Pre-Hospital Care." Cuestiones de Fisioterapia 53, no. 02 (2024): 589–96. https://doi.org/10.48047/yjzx3s59.

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Background: Pre-hospital care plays a critical role in improving patient outcomes during emergencies. With technological advances, integrating telemedicine and artificial intelligence (AI) into paramedic services has the potential to transform how emergency services are delivered. Methods: This systematic review followed PRISMA guidelines. A comprehensive search was conducted in PubMed, Scopus, Web of Science, and IEEE Xplore for studies published between 2016 and 2024. Eligible studies assessed the use of telemedicine and/or AI by paramedics in pre-hospital settings.

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Albahar, Alreem. "How AI Improves Telemedicine through Improving Data Management in Healthcare." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 3 (2023): 242–50. http://dx.doi.org/10.60087/jklst.vol2.n3.p250.

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The ability of artificial intelligence (AI) to greatly increase the efficacy and efficiency of any task carried out has contributed to its rise in popularity in recent years. These days, the healthcare industry uses AI more often because of the growth in data and complexity. This study, which examined artificial intelligence (AI) in the healthcare industry, sought to fully grasp how AI enhances telemedicine by optimising data management. The results indicate that AI has helped to improve fragmented data organisation and data management. This enhancement really helped to increase the efficacy a

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Park, Yu Seong, Kyeong Heon Lee, Hye In Jeong, and Kyeong Han Kim. "The Necessity of Education in Response to Technological Advancements and Future Environmental Changes: A Comparison of Korean Medicine Doctors and Students." Journal of Korean Medicine 44, no. 4 (2023): 72–86. http://dx.doi.org/10.13048/jkm.23048.

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Objectives: The medical field is rapidly evolving with AI and digital technologies like AI-based X-ray analysis and digital therapeutics gaining approval. Telemedicine is becoming prominent, and medical schools are adapting by integrating AI education. Pusan National University leads a talent training project for AI in health. Korean Medicine is incorporating AI with diagnostic systems and chatbots. However, there's a lack of research on education awareness in Korean Medicine Colleges. The study aims to assess opinions on integrating AI, digital therapeutics, and DNA test into the Korean medic

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Seliverstov, P., and G. Brudyan. "Opportunities for artificial intelligence and telemedicine in implantology." 34 34, no. 6 (2023): 85–87. http://dx.doi.org/10.29296/25877305-2023-06-18.

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Artificial Intelligence (AI) has been making significant strides in various fields, including healthcare. One such area is dental implantology. AI can assist in accurate diagnosis, treatment planning, in the execution of the procedure, and predict implant success based on various factors like bone density, implant site, patient's medical history, etc. Despite the promising potential, the application of AI in dental implantology is still in its nascent stages. Research in this area of medicine is limited, but there has been an increase in recent years. This trend is related to the possibility o

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Seliverstov, P., G. Brudyan, and V. Mikhailov. "Application of artificial intelligence and telemedicine in dentistry: prospects and review." Vrach 34, no. 5 (2023): 94–97. http://dx.doi.org/10.29296/25877305-2023-05-17.

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The use of artificial intelligence (AI) in dentistry is a promising field that has the potential to revolutionize the healthcare sector and improve the quality of dental care. Researchers are also discussing methods of telemedicine health screening, including the use of questionnaires and AI to analyze the data obtained. AI can be used to automatically analyze X-rays and detect dental and gum disease, such as cavities, periodontitis and others. AI can help determine the best therapy and medication dosage for each patient based on his or her individual characteristics. Moreover, AI can be used

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Burrell, Darrell Norman. "Dynamic Evaluation Approaches to Telehealth Technologies and Artificial Intelligence (AI) Telemedicine Applications in Healthcare and Biotechnology Organizations." Merits 3, no. 4 (2023): 700–721. http://dx.doi.org/10.3390/merits3040042.

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The COVID-19 pandemic has ushered in an unprecedented adoption and integration of telehealth and artificial intelligence (AI) driven by telemedicine technologies into healthcare systems worldwide. These innovations promise to revolutionize healthcare delivery by offering greater accessibility, efficiency, and responsiveness to patient needs. However, the rapid deployment of these technologies in response to the crisis has illuminated the imperative need for systematic evaluation processes that comprehensively assess their operations and outcomes. This article underscores the critical importanc

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Bagus Alfrisa, Muhammad Reza Fahlevi Hanafi, and Yuni Suharnida Lubis. "Literature Review Dampak Artificial Intelligence terhadap Peningkatan Kualitas Perawatan Pasien." JURNAL RISET RUMPUN ILMU KESEHATAN 4, no. 2 (2025): 164–72. https://doi.org/10.55606/jurrikes.v4i2.5383.

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The integration of telemedicine and artificial intelligence (AI) into critical care has emerged as a revolutionary development in the healthcare sector, aiming to enhance patient care and outcomes. This research aims to explore the impact of these technologies on improving the quality of patient care in intensive care units (ICUs). A systematic review of recent studies published between 2018 and 2023 was conducted to analyze the role of telemedicine in improving access to healthcare and the application of AI in enhancing diagnostic accuracy and monitoring patients in real-time. The findings su

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Mitronin, A. V., T. A. Abakarov, G. M. A. Budaichiev, and E. R. Osmanov. "Artificial intelligence in endodontics: current achievements and future prospects. A literature review." Endodontics Today 23, no. 1 (2025): 62–70. https://doi.org/10.36377/et-0063.

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INTRODUCTION. The article explores the current achievements and future prospects of artificial intelligence (AI) in endodontics, emphasizing its applications in diagnostics, treatment planning, quality control, outcome prediction, telemedicine, and educational processes. AI is highlighted as a transformative tool that enhances precision, standardization, and personalization in endodontic practice.AIM. To systematically analyze the current state of AI application in endodontics and outline directions for further research and implementation.MATERIALS AND METHODS. The study involved a thorough re

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