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Relevant bibliographies by topics / AI Telemedicine

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Academic literature on the topic 'AI Telemedicine'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "AI Telemedicine"

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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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Books on the topic "AI Telemedicine"

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Rammler, Roman. AI-Automated Telemedicine - a New Approach to Remote Patient Monitoring: Distributed Artificial/Augmented Intelligence - AI - the Future of Healthcare. Independently Published, 2021.

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Davenport, Thomas H., and Steven M. Miller. Working with AI. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14453.001.0001.

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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, m

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Book chapters on the topic "AI Telemedicine"

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Thakur, Deepak, Tanya Gera, Chetna Kaushal, Ankit Bansal, and Sunil Gupta. "The Power of AI in Telemedicine." In Handbook on Augmenting Telehealth Services. CRC Press, 2023. http://dx.doi.org/10.1201/9781003346289-5.

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Joseph, Asha, and Shiju George. "Human Disease Prediction System – Application of AI Techniques in Chronic Diseases." In Artificial Intelligence in Telemedicine. CRC Press, 2023. http://dx.doi.org/10.1201/9781003307778-11.

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Sharma, Hitesh Kumar, Ravi Tomar, Preeti, and Prashant Ahlawat. "AI-Enabled Cloud-Based Intelligent System for Telemedicine." In Mathematical Modeling for Intelligent Systems. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003291916-5.

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Owoyemi, Ayomide, Eugeniah Arthur, Tope Ladi-Akinyemi, Yemisi Babalola, and Damian Okaibedi Eke. "Trustworthy AI in Healthcare: Exploring Ethics in Digital Health Technologies in Nigeria." In Trustworthy AI. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-75674-0_9.

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Abstract The rapid expansion of digital health solutions in Africa, encompassing telemedicine, AI, and other technologies, aligns with WHO’s Goals for Sustainable Development and Universal Health Coverage. Despite its benefits, this growth raises ethical concerns regarding deploying these technologies. A cross-sectional survey targeting executives of Nigerian digital health startups was conducted using Google Forms. The survey focused on startup characteristics, data management, ethical/legal governance, and user engagement. Data analysis employed descriptive statistics and cross-tabulation in

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Brati, Esmeralda. "Factors Affecting the Use of Telemedicine: An Empirical Analysis." In AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-42085-6_3.

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Adeva, J. J. García, J. M. Pikatza, S. Flórez, and F. J. Sobrado. "Intrusion Detection Using Text Mining in a Web-Based Telemedicine System." In AI 2005: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11589990_131.

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Han, Suyeon, and Deawoo Park. "Telemedicine AI App for Prediction of Pets Joint Diseases." In Studies in Computational Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64769-8_11.

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Undheim, Trond Arne. "Digital Health Tech—Telemedicine and AI, Wearables, Social Media, Digital Therapeutics." In Health Tech. Productivity Press, 2021. http://dx.doi.org/10.4324/9781003178071-2.

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Lin, Tzu-Wei, and Chien-Lung Hsu. "Privacy-Preserved Hierarchical Authentication and Key Agreement for AI-Enabled Telemedicine Systems." In 2021 International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05491-4_14.

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Jena, Biranchi, Babasaheb Jadhav, Satish Khalikar, and Apeksha Nagawade. "Methodological and Analytical Considerations for Development and Implementation of an Audit System for Telemedicine." In Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem. CRC Press, 2023. http://dx.doi.org/10.1201/9781003356189-18.

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Conference papers on the topic "AI Telemedicine"

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Filogna, Silvia, Alessio Malizia, Daniele Mazzei, Giuseppe Prencipe, Giuseppina Sgandurra, and Tommaso Turchi. "Telemedicine and AI: From Co-Design to Explainability." In 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI). IEEE, 2024. http://dx.doi.org/10.1109/rtsi61910.2024.10761199.

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Thangalakshmi, S., N. Mohankumar, L. N. Jayanthi, Y. M. Blessy, R. Meenakshi, and M. Rajmohan. "Telemedicine Platforms with Cloud-Based AI-Driven Diagnostics in Hospitals." In 2025 International Conference on Visual Analytics and Data Visualization (ICVADV). IEEE, 2025. https://doi.org/10.1109/icvadv63329.2025.10961133.

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Dhatrak, Manish, Samarth Jadhav, Sumeet Gupta, and Naseemuddin Siddiqui. "AI-Enhanced Stethoscope for Real Time Cardiopulmonary Diagnostics and Telemedicine Integration." In 2025 3rd International Conference on Advancement in Computation & Computer Technologies (InCACCT). IEEE, 2025. https://doi.org/10.1109/incacct65424.2025.11011421.

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Vieira, Rita Duarte, Adriana Arrais, Duarte Dias, Carolina Soares, João Massano, and João Paulo Silva Cunha. "Creating the Next Digital Telemedicine Tool for Parkinson's Disease Management with AI." In 2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 2024. https://doi.org/10.1109/bhi62660.2024.10913661.

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Ranganathan, Chitra Sabapathy, D. Sethuraman, M. A. Manivasagam, Soundharya K, T. Yuvaraj, and M. Rajmohan. "IoT-Driven Telepresence Robots for Telemedicine using AI for Improved Patient Interaction." In 2024 First International Conference on Innovations in Communications, Electrical and Computer Engineering (ICICEC). IEEE, 2024. https://doi.org/10.1109/icicec62498.2024.10808988.

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Chand, Repu Dhaman, Ranjana Rajnish, Hem Chandra, Priyanka Tiwari, and Prasanta Kumar Pradhan. "Building an AI-Driven Symptom Checker Using Python Django for Enhanced Telemedicine Services." In 2025 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2025. https://doi.org/10.1109/icict64420.2025.11005056.

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Misal, Sachin Ramchandra, Lavanya Mohan, Suresh Kumar Sundararajan, Balakrishna Bathala, Saheli Majumdar, and C. Sivakumar. "Telemedicine and Remote Patient Monitoring: Enhancing Access to Healthcare Through IoT and AI Technologies." In 2025 First International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT). IEEE, 2025. https://doi.org/10.1109/ce2ct64011.2025.10941287.

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Woodward, Dexter, Lubna Kamal, Sreekar Peddi, Debabrata Baral, Tania Thomas, and Sibi K. "Telemedicine and AI: Revolutionizing Healthcare Access Through Advanced Electronics in Rural and Underserved Regions." In 2025 First International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT). IEEE, 2025. https://doi.org/10.1109/ce2ct64011.2025.10939937.

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S, Harshithan K., and Babymol Kurian. "Medico Bot: AI based Telemedicine System with Disease Diagnosis and Expert Recommendation System with Blockchain Implementation." In 2024 Second International Conference on Inventive Computing and Informatics (ICICI). IEEE, 2024. http://dx.doi.org/10.1109/icici62254.2024.00041.

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Jasim, Abdulrahman Ahmed, Oguz Ata, and Omar Hussein Salman. "AI-Driven Triage: A Graph Neural Network Approach for Prehospital Emergency Triage Patients in IoMT-Based Telemedicine Systems." In 2024 International Symposium on Electronics and Telecommunications (ISETC). IEEE, 2024. https://doi.org/10.1109/isetc63109.2024.10797314.

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