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Artykuły w czasopismach na temat „Healthcare AI”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Chinta, Sribala Vidyadhari, Zichong Wang, Avash Palikhe, et al. "AI-driven healthcare: Fairness in AI healthcare: A survey." PLOS Digital Health 4, no. 5 (2025): e0000864. https://doi.org/10.1371/journal.pdig.0000864.

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Artificial intelligence (AI) is rapidly advancing in healthcare, enhancing the efficiency and effectiveness of services across various specialties, including cardiology, ophthalmology, dermatology, emergency medicine, etc. AI applications have significantly improved diagnostic accuracy, treatment personalization, and patient outcome predictions by leveraging technologies such as machine learning, neural networks, and natural language processing. However, these advancements also introduce substantial ethical and fairness challenges, particularly related to biases in data and algorithms. These b

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Mahadev Mastud. "AI in HealthCare." International Journal of Scientific Research in Science and Technology 12, no. 1 (2025): 34–36. https://doi.org/10.32628/ijsrst25121152.

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Artificial Intelligence (AI) is revolutionizing the healthcare industry by enhancing diagnostics, streamlining workflows, and enabling more personalized patient care. By leveraging powerful algorithms and vast amounts of data, AI can identify patterns, predict outcomes, and assist healthcare professionals in making informed decisions. This introduction explores the transformative role of AI in healthcare, highlighting its applications, benefits, challenges, and potential for future advancements. From improving diagnostic accuracy to optimizing administrative processes, AI is reshaping the way

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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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Satpute, Ms Puja D. "Healthcare Chatbot Using AI." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 5846–51. http://dx.doi.org/10.22214/ijraset.2024.61249.

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Abstract: Medical chatbots mark a major advancement in patient care and dissemination of medical information. These AIpowered virtual assistants provide a variety of services, from providing medical information, facilitating appointments, and monitoring symptoms to providing psychological support and making it easier to find the nearest medical centre. It provides users with 24/7 access by easily advertising and pre-registering, improving user experience and making the healthcare process more efficient. Although medical chatbots have many advantages, it is important to know that their role is

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Talati, Dhruvitkumar. "AI in healthcare domain." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 3 (2023): 256–62. http://dx.doi.org/10.60087/jklst.vol2.n3.p253.

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Artificial Intelligence (AI) has emerged as a transformative force in the healthcare domain, revolutionizing various aspects of medical research, diagnostics, treatment, and patient care. This paper provides an overview of recent developments and applications of AI in healthcare, highlighting its potential to enhance efficiency, accuracy, and accessibility in medical practices. The integration of machine learning algorithms, natural language processing, and computer vision techniques has enabled AI systems to analyze vast amounts of medical data, support clinical decision-making, and personali

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Talati, Dhruvitkumar. "AI in healthcare domain." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 3 (2023): 256–62. http://dx.doi.org/10.60087/jklst.vol2.n3.p262.

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Artificial Intelligence (AI) has emerged as a transformative force in the healthcare domain, revolutionizing various aspects of medical research, diagnostics, treatment, and patient care. This paper provides an overview of recent developments and applications of AI in healthcare, highlighting its potential to enhance efficiency, accuracy, and accessibility in medical practices. The integration of machine learning algorithms, natural language processing, and computer vision techniques has enabled AI systems to analyze vast amounts of medical data, support clinical decision-making, and personali

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Saiteja, Kobbaji. "Healthcare Chatbot Using AI." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49884.

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Abstract - In today's era, India faces a major challenge in providing affordable and accessible healthcare, especially in rural areas where transport and quality facilities are limited. To address this, we developed an AI-powered Healthcare Chatbot using Python. This system helps users get instant responses to health-related queries and locate nearby doctors, clinics, and hospitals using the Google Places API—crucial during emergencies. The project has two modules: User and Admin. Users can register, log in, manage profiles, chat with the bot, and access healthcare facility information. Admins

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Anand, Laxman Mhatre. "AI automation in healthcare." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 12, no. 2 (2024): 1–4. https://doi.org/10.5281/zenodo.14208968.

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As the demand for healthcare services surges, the industry is becoming increasingly vulnerable to issues such as patient engagement challenges, data overload, and diagnosis and prescription hurdles. AI automation is a novel technology that promises to address these challenges. This document discusses some of the challenges in healthcare and how AI automation mitigates these issues.

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Vishal, Ananda Kuwar, Mahesh Asawa Parth, Ravindra Patil Ganesh, Nandkumar Pawar Vedant, Jain Preeti, and Yedurkar Amit. "AI Driven Healthcare Solution." TIJER - INTERNATIONAL RESEARCH JOURNALS 12, no. 2 (2025): a117—a121. https://doi.org/10.5281/zenodo.15209814.

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Artificial Intelligence (AI) is transforming the healthcare sector by providing innovative, data-centric solutions to various medical challenges. This project aims to develop spe- cialized AI agents tailored for healthcare applications, focusing on creating systems such as Ortho AI for orthopedic-related queries and Dermatology AI for skin-related issues. These AI solutions provide patients with accurate, personalized healthcare advice, supporting them in obtaining quicker, more reliable responses. Additionally, they assist healthcare professionals by enhancing diagnosis and treatment recommen

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Pagidoju, Vijaybhasker. "RELIABLE AI SYSTEMS IN HEALTHCARE (AI MEETS SRE)." INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY 16, no. 2 (2025): 37–58. https://doi.org/10.34218/ijcet_16_02_003.

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Väänänen, Antti, Keijo Haataja, and Pekka Toivanen. "Survey to healthcare professionals on the practicality of AI services for healthcare." F1000Research 9 (July 22, 2020): 760. http://dx.doi.org/10.12688/f1000research.23883.1.

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Background: Artificial Intelligence (AI) is already in use in many fields of healthcare, and utilization of AI in state-of-the art healthcare services is growing, with many studies showing that AI can provide benefits in healthcare processes. However, there is a need for research about healthcare professionals’ willingness to use AI-based services, and their consideration about in which cases AI could provide better healthcare outcomes and reduce healthcare professionals’ workload. Methods: We studied the latest technologies and methods from current healthcare AI services’ end-users to create

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Hulsen, Tim, and Mark Scheper. "AI in Healthcare: Do Not Forget About Allied Healthcare." AI 6, no. 6 (2025): 114. https://doi.org/10.3390/ai6060114.

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Artificial intelligence, the simulation of human intelligence by computers and machines, has found its way into healthcare, helping surgeons, doctors, radiologists, and many more. However, over 80% of healthcare professionals consists of people working in allied health professions such as nurses, physiotherapists, and midwives. Considering the aging of the general population around the world, the workforce shortages in these occupations are especially crucial. As the COVID-19 pandemic demonstrated, globally, most healthcare systems are strained, and there is a consensus that current healthcare

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Navath, Suryakiran. "Transforming Healthcare: The Impact and Future of Artificial Intelligence in Healthcare." Journal of Artificial intelligence and Machine Learning 1, no. 1 (2023): 16–21. http://dx.doi.org/10.55124/jaim.v1i1.234.

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The integration of Artificial Intelligence (AI) in healthcare has ushered in a new era, transforming the industry in unprecedented ways. This manuscript delves into the profound impact of AI on healthcare systems and envisions its future trajectory. Through a comprehensive analysis of current applications, challenges, and emerging trends, this study illuminates the revolutionary changes brought about by AI technologies. From advanced diagnostics to personalized treatment plans, AI is reshaping patient care, improving operational efficiency, and fostering innovative solutions. Furthermore, the

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Tahseen, Shazma, Husan Bano Channar, Urooj Bhatti, Tasleem Akhtar Laghari, Sana Areej, and Shah Muhammad Kamran. "Unveiling Healthcare Practitioners' Knowledge and Acceptance of Artificial Intelligence in Healthcare." Journal of Health and Rehabilitation Research 4, no. 2 (2024): 859–64. http://dx.doi.org/10.61919/jhrr.v4i2.889.

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Background: The rapid advancement of artificial intelligence (AI) is poised to revolutionize healthcare delivery systems profoundly. With its capacity to enhance diagnostics, treatment, and patient care, understanding AI's role and integration in healthcare is crucial for medical professionals and students. Objective: This study aims to assess the familiarity, knowledge, and comprehension of AI among medical students and physicians, identifying both challenges and opportunities associated with its use in medicine. Methods: A structured questionnaire, adapted from established scales, was used t

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Shah, Yamini D., Shailvi M. Soni, and Manish P. Patel. "Artificial intelligence in healthcare." Indian Journal of Pharmacy and Pharmacology 8, no. 2 (2021): 102–15. http://dx.doi.org/10.18231/j.ijpp.2021.018.

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Artificial Intelligence (AI) is described as a field of science and engineering that is concerned with the artificial appreciation of what is generally referred to as prudent behavior and the formation of fascinations that demonstrate such conduct. AI is an expansive concept that encloses a series of advances (a considerable lot of which have been being worked on for quite a few years) that are expected to use human-like insight to handle the problems. Right now in combination with enhanced AI developments like extreme or significantly more engaged, we are experiencing a renewed enthusiasm for

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Ramachandran Sumangala Devi, Arun Kumar. "Enhancing Healthcare Quality with AI-Based Performance Metrics." Global Research and Development Journals 5, no. 12 (2020): 41–48. http://dx.doi.org/10.70179/grdjev09i120092.

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Artificial intelligence (AI) based management holds promise across healthcare by managing and enabling the delivery of the right care to the right patient at the right time. AI-based performance metrics are essential to managing delivery and enhancing both care quality and patient experience. Algorithmic insight into the uncertainty of diagnosis and patient care is aided by a framework termed Human+AI. This perspective describes the roles of AI agents, health systems, patients, and regulators. AI agent roles and relationships revolve around the therapeutic process and an AI process that sorts

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Reddy, Sandeep, John Fox, and Maulik P. Purohit. "Artificial intelligence-enabled healthcare delivery." Journal of the Royal Society of Medicine 112, no. 1 (2018): 22–28. http://dx.doi.org/10.1177/0141076818815510.

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Summary In recent years, there has been massive progress in artificial intelligence (AI) with the development of deep neural networks, natural language processing, computer vision and robotics. These techniques are now actively being applied in healthcare with many of the health service activities currently being delivered by clinicians and administrators predicted to be taken over by AI in the coming years. However, there has also been exceptional hype about the abilities of AI with a mistaken notion that AI will replace human clinicians altogether. These perspectives are inaccurate, and if a

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Ashfaq, Zarlish, Rafia Mumtaz, Abdur Rafay, et al. "Embedded AI-Based Digi-Healthcare." Applied Sciences 12, no. 1 (2022): 519. http://dx.doi.org/10.3390/app12010519.

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Healthcare is an indispensable part of human life and chronic illnesses like cardiovascular diseases (CVD) have a deeply negative impact on the healthcare sector. Since the ever-growing population of chronic patients cannot be managed at hospitals, therefore, there is an urgent need for periodic monitoring of vital parameters and apposite treatment of these patients. In this paper, an Internet of Medical Things (IoMT) -based remote patient monitoring system is proposed which is based on Artificial Intelligence (AI) and edge computing. The primary focus of this paper is to develop an embedded p

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Gifu, Daniela. "AI-backed OCR in Healthcare." Procedia Computer Science 207 (2022): 1134–43. http://dx.doi.org/10.1016/j.procs.2022.09.169.

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Mhatre, Anand Laxman. "Gen AI governance in healthcare." Journal of Artificial Intelligence, Machine Learning and Data Science 2, no. 4 (2024): 1880–82. https://doi.org/10.51219/jaimld/anand-laxman-mhatre/416.

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T, Santhosh. "AI in Healthcare and Medicine." International Journal of Scientific Research and Engineering Trends 10, no. 6 (2024): 2853–57. https://doi.org/10.61137/ijsret.vol.10.issue6.387.

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Neha, Fnu, Deepshikha Bhati, Deepak Kumar Shukla, and Md Amiruzzaman. "ChatGPT: Transforming Healthcare with AI." AI 5, no. 4 (2024): 2618–50. https://doi.org/10.3390/ai5040126.

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ChatGPT, developed by OpenAI, is a large language model (LLM) that leverages artificial intelligence (AI) and deep learning (DL) to generate human-like responses. This paper provides a broad, systematic review of ChatGPT’s applications in healthcare, particularly in enhancing patient engagement through medical history collection, symptom assessment, and decision support for improved diagnostic accuracy. It assesses ChatGPT’s potential across multiple organ systems and specialties, highlighting its value in clinical, educational, and administrative contexts. This analysis reveals both the benef

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Alan Varghese, Jefin Varghese, Jubin Biju, Roshan Thomas, and Merlin Thomas. "Explainable AI in Healthcare Applications." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 12 (2024): 3671–79. https://doi.org/10.47392/irjaem.2024.0545.

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The entry of artificial intelligence into health care systems brings unprecedented advances in diagnosing, personalized treatment, and predictive analytics. Many of these AI models, especially the deep-learning algorithms, have been referred to as "black boxes" and raise gigantic questions about trust, transparency, and reliability in clinical settings. Therefore, explainable AI answers the challenges by drawing to the fore methodologies that make AI models more interpretable, thereby making them more accepted and usable in the fraternity of health. It engages with XAI in healthcare by scrutin

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Carey, Siân, Allan Pang, and Marc de Kamps. "Fairness in AI for healthcare." Future Healthcare Journal 11, no. 3 (2024): 100177. http://dx.doi.org/10.1016/j.fhj.2024.100177.

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Bhopale, Pranita Pravin, Tejas Pankaj Patil, Devesh Ravindra Choudhari, and Bhavana Zambare. "AI-HealthCare Chat-Bot System." International Journal of Innovations in Engineering and Science 9, no. 4 (2024): 30–34. http://dx.doi.org/10.46335/ijies.2024.9.4.6.

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Gupta, Diya. "AI-ML based HealthCare Chatbot." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41352.

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In the realm of modern healthcare, the exigency for instantaneous, accurate, and personalized medical assistance remains a paramount concern, primarily due to infrastructural deficits and delayed medical interventions, especially in remote locales. The AI-ML-powered healthcare chatbot aspires to ameliorate this predicament by offering 24/7 medical support, ranging from symptom assessment to scheduling consultations and medication reminders, thereby fortifying healthcare accessibility. The focal point of this inquiry entails a meticulous exploration of the underlying factors contributing to del

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Y., Sri Lalitha, Ganapathi Raju N.V., Ram Teja Vanimireddy, Venkata Sai Kiran Mothe, and Anil Nayak Nenavath. "Conversational AI Chatbot for HealthCare." E3S Web of Conferences 391 (2023): 01114. http://dx.doi.org/10.1051/e3sconf/202339101114.

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Health is a state of total physical, mental, and social wellbeing. chatbots have been applied to this industry frequently and in a variety ofways in the past, there is still room for more inventive uses. Healthcareconversational AI use cases are flexible and may be tailored to the industry. Patients might use them to gain additional knowledge about their disease, the therapies that are available, or even their insurance coverage. Because research has shown that healthcare chatbots can improve patient satisfaction and significantly reduce wait times, many healthcare organisations are considerin

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Bhattacharya, Subh. "AI Set to Transform Healthcare." New Electronics 53, no. 9 (2020): 22–23. http://dx.doi.org/10.12968/s0047-9624(22)61243-4.

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B.S., Prof Biradar. "AI HealthCare Chat Bot System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29592.

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Through chatbots one can communicate with text or voice interface and get reply through artificial intelligence. Typically, a chat bot will communicate with a real person Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It als

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Aadil, Gauri Muhammed, and Shaikh Mohd Maaz. "Human-AI-Collaboration in Healthcare." International Journal for Research in Applied Science and Engineering Technology 12, no. 1 (2024): 479–84. http://dx.doi.org/10.22214/ijraset.2024.57939.

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Abstract: This research paper explores how teaming up humans with Artificial Intelligence (AI) can make healthcare even better. Imagine doctors, nurses, and AI systems working side by side like a dream team! We dive into this exciting collaboration to see how it can boost the accuracy of diagnoses, improve treatments, and make patients healthier. Additionally, more theory-driven research is needed to inform the design, implementation, and use of collaborative AI for healthcare and to realize its benefits We take a close look at the cool technologies AI brings to the healthcare table, like supe

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GOAPAL, DR NAND. "Impact of AI in Healthcare." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45259.

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Abstract: Artificial Intelligence in Healthcare Artificial Intelligence (AI) is revolutionizing the healthcare industry by enabling smarter diagnostics, personalized treatments, efficient workflows, and data-driven decision-making. Through technologies such as machine learning, natural language processing, and computer vision, AI systems can analyze vast volumes of medical data to identify patterns, predict outcomes, and assist clinicians in making accurate diagnoses.

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Shaikh, Umar. "AI-Based Healthcare Chatbot System." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5510–13. https://doi.org/10.22214/ijraset.2025.69526.

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This healthcare chatbot, powered by artificial intelligence, is built to reduce the communication gap between patients and healthcare professionals, particularly in regions with limited access to medical services. It delivers quick responses for medical queries, supports in urgent scenarios, and offers mental wellness assistance. The integration of natural language processing (NLP) allows individuals to express their health concerns in their native language, improving the clarity of symptom interpretation and enabling customized medical suggestions. Furthermore, the system helps users schedule

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Mahor, Harshita, and Surbhi Gupta. "Design a AI Healthcare Chatbot." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 890–95. https://doi.org/10.22214/ijraset.2025.70067.

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Abstract : The Artificial Intelligence (AI) chatbots have emerged as transformative tools in the healthcare sector, enhancing patient engagement, automating routine tasks, and improving healthcare accessibility. This paper explores the development of AI-driven chatbots for healthcare, analyzing their significance, methodologies, and impact on patient care. Through a comprehensive literature review and experimental evaluation, this study presents insights into the effectiveness of healthcare chatbots and the challenges they face, including ethical concerns and data security. The results indicat

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Jadhav, Amol. "AI-ML based HealthCare Chatbot." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47519.

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Abstract - The demand for efficient, accessible, and scalable healthcare solutions has prompted the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies into medical systems. AI-ML-based healthcare chatbots represent a transformative innovation, providing real-time, personalized medical assistance through conversational interfaces. These chatbots leverage Natural Language Processing (NLP) and machine learning algorithms to analyze symptoms, offer preliminary diagnoses, schedule consultations, and deliver medication reminders, thus enhancing healthcare accessibilit

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Warren, Luke. "Digital scalpel: AI in healthcare." Bulletin of the Royal College of Surgeons of England 107, no. 5 (2025): 244–45. https://doi.org/10.1308/rcsbull.2025.84.

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Kaur, Simrandzhit. "Multiagents AI Systems In Healthcare." International Journal of Science, Engineering and Technology 13, no. 3 (2025): 1–5. https://doi.org/10.61463/ijset.vol.13.issue3.272.

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Sawant, Devika. "AI in Medical." International Journal for Research in Applied Science and Engineering Technology, no. 6 (June 30, 2024): 168–75. http://dx.doi.org/10.22214/ijraset.2024.63010.

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Abstract: Artificial Intelligence (AI) stands as a transformative influence in the realm of medicine, poised to reshape healthcare delivery and elevate patient outcomes. This summary offers an overview of AI's impact on medical applications, with key technologies such as machine learning, natural language processing, and computer vision playing pivotal roles across various healthcare domains, from diagnostics to treatment planning and patientcare. A notable stride in this evolution is the integration of AI-driven telemedicine solutions, effectively expanding access to healthcare services, part

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Pawan, Joshi, Tiwari Shubhangi, Bhatt Sanjay, and Sati Bindu. "Artificial Intelligence in Healthcare: From Diagnostics to Personalized Medicine And Beyond." International Journal of Pharmaceutical and Clinical Research 16, no. 9 (2024): 68–72. https://doi.org/10.5281/zenodo.13885454.

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Artificial intelligence (AI) is being increasingly integrated into healthcare systems to enhance treatment, diagnosis, and patient care. This review evaluates the significant applications of AI in healthcare, particularly its impact on medical imaging, genomics, and early diagnosis, as well as its role in reducing errors and increasing efficiency. Deep learning, Machine learning, and natural language processing (NLP) are among the most impactful AI technologies being deployed. While AI holds immense promise, challenges, such as ethical concerns, bias, and regulatory hurdles, must be addressed

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Kamolova, F. E., D. X. Buvayeva, S. M. Matmusayeva, and J. A. Djuraev. "THE ROLE OF AI IN HEALTHCARE INDUSTRY." International Journal of Medical Sciences And Clinical Research 4, no. 9 (2024): 20–25. http://dx.doi.org/10.37547/ijmscr/volume04issue09-04.

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This article analyses the present condition of technological applications based on artificial intelligence (AI) and their influence on the healthcare sector. This work conducted a comprehensive literature research and examined certain real-world instances of AI implementations in the healthcare sector. Undoubtedly, the fast progress of artificial intelligence (AI) and associated technologies will enable healthcare providers to provide fresh value for their patients and enhance the effectiveness of their internal operations. However, successful deployment of AI will always pose distinct problem

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Kamolova, F. E., D. X. Buvayeva, S. M. Matmusayeva, and J. A. Djuraev. "THE ROLE OF AI IN HEALTHCARE INDUSTRY." International Journal of Medical Sciences And Clinical Research 4, no. 9 (2024): 20–25. http://dx.doi.org/10.37547/ijmscr/volume04issue09-04a.

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This article analyses the present condition of technological applications based on artificial intelligence (AI) and their influence on the healthcare sector. This work conducted a comprehensive literature research and examined certain real-world instances of AI implementations in the healthcare sector. Undoubtedly, the fast progress of artificial intelligence (AI) and associated technologies will enable healthcare providers to provide fresh value for their patients and enhance the effectiveness of their internal operations. However, successful deployment of AI will always pose distinct problem

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Reddy Desani, Nithin, and Srujan Reddy Jabbi Reddy. "Data Engineering Challenges in AI for Healthcare." International Journal of Science and Research (IJSR) 11, no. 1 (2022): 1647–52. http://dx.doi.org/10.21275/es22106103914.

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Kailash, Alle. "AI in Healthcare: Predictive Analytics and Diagnostics." Journal of Scientific and Engineering Research 7, no. 9 (2020): 233–37. https://doi.org/10.5281/zenodo.13347491.

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Predictive analytics and decision support systems are changing patient care in artificial intelligence (AI) in healthcare. Through the identification of trends and risk variables, predictive analytics ease early illness prevention and diagnosis, improving patient outcomes and enabling cost-effective healthcare. By using unique patient data to create customized therapies that maximize benefits and reduce side effects, machine learning enables individualized treatment strategies. AI-driven algorithms improve diagnostic precision in medical imaging by delivering quick and correct evaluations. Hea

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Aqeel, Ubada, Manisha Sharma, and Shibu John. "Artificial intelligence in healthcare : A comprehensive survey of healthcare professionals in India." Journal of Information and Optimization Sciences 46, no. 3 (2025): 669–88. https://doi.org/10.47974/jios-1679.

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Objective: Artificial intelligence (AI) is widely recognized as a transformative force that is expected to significantly influence patient care in the near future.This study aims to evaluate the level of awareness regarding AI technologies among healthcare professionals in India, as well as to explore their perceptions of AI’s potential applications in medical practice. Design: An online survey using Google Forms was administered to healthcare professionals employed at prominent hospitals in Delhi, India. Setting: Invitations to complete the online questionnaire were sent via email exclusively

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Bhagat, Shrey. "Artificial Intelligence in Healthcare." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 309–11. http://dx.doi.org/10.22214/ijraset.2021.37319.

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Artificial intelligence aspires to imitate the psychological functions of humans. It ushers in a perfect change in care, fueled by the rising accessibility of care information and the rapid advancement of analytics approaches. We prefer to assess the current state of AI applications in healthcare and speculate on their future. AI is being used to apply a wide range of care expertise. Machine learning algorithms for structured knowledge, such as the traditional support vector machine and neural network, and therefore the popular deep learning, as well as the tongue process for unstructured know

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Zhang, Ziyi. "Artificial Intelligence in Healthcare." Journal of Computing and Electronic Information Management 15, no. 3 (2024): 93–95. https://doi.org/10.54097/xfaemy47.

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This paper discusses the development history of artificial intelligence (AI) technology and its application in the medical field, including its progress in medical image analysis, intelligent diagnosis, drug development and genomics. It analyses how AI technology breaks through the imbalance between the supply and demand of medical resources, reduces the misdiagnosis rate, and promotes scientific medical decision-making. The application of AI technology in medical data processing and analysis is demonstrated through a case study of Mediadu Cloud, and its advantages and challenges are discussed

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Kudirat, O. Alli, O. Adewale Adeola, and O. Akintajuwa Ademola. "Exploring the Opportunities and Challenges of Artificial Intelligence in Healthcare: A Study of Healthcare Workers in Medical Institutions in Akure, Ondo State, Nigeria." Journal of Economics, Finance And Management Studies 08, no. 02 (2025): 988–1000. https://doi.org/10.5281/zenodo.14869166.

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A total of 200 health care workers (32 medical doctor, 77 nurses, 46 allied health e.g., physiotherapy etc., 30 administrative officers, and 15 others hospital officers). Outcomes revealed that healthcare workers generally have a strong awareness of AI technologies, with a majority believing in their potential to improve healthcare delivery with different standard deviation indicating variation in opinion (σ=0.71867, σ=1.18142, σ=0.83237, σ=0.83237.). Healthcare workers generally have a positive perception of AI's potential to improve patient care and healthcare deliver

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Raheja, Dev. "System Safety in Healthcare." Journal of System Safety 57, no. 1 (2021): 4–5. http://dx.doi.org/10.56094/jss.v57i1.3.

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The purpose of system safety is to prevent bad things from happening. Lately, systems have been using artificial intelligence (AI), and verification and validation is becoming a major challenge. First, we have to understand the four main types of AI, in addition to much-less-used methods on the web. The main types of AI are:  Reactive Machines Limited Memory Theory of Mind Self-aware 

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Väänänen, Antti, Keijo Haataja, Katri Vehviläinen-Julkunen, and Pekka Toivanen. "AI in healthcare: A narrative review." F1000Research 10 (October 8, 2021): 6. http://dx.doi.org/10.12688/f1000research.26997.2.

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In this paper, we focus on providing a narrative review of healthcare services in which artificial intelligence (AI) based services are used as part of the operations and analyze key elements to create successful AI-based services for healthcare. The benefits of AI in healthcare are measured by how AI is improving the healthcare outcomes, help caregivers in work, and reducing healthcare costs. AI market in healthcare sector have also a high market potential with 28% global compound annual growth rate. This paper will collect outcomes from multiple perspectives of healthcare sector including fi

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Väänänen, Antti, Keijo Haataja, Katri Vehviläinen-Julkunen, and Pekka Toivanen. "AI in healthcare: A narrative review." F1000Research 10 (January 6, 2021): 6. http://dx.doi.org/10.12688/f1000research.26997.1.

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In this paper, we focus on providing a narrative review of healthcare services in which artificial intelligence (AI) based services are used as part of the operations and analyze key elements to create successful AI-based services for healthcare. The benefits of AI in healthcare are measured by how AI is improving the healthcare outcomes, help caregivers in work, and reducing healthcare costs. AI market in healthcare sector have also a high market potential with 28% global compound annual growth rate. This paper will collect outcomes from multiple perspectives of healthcare sector including fi

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Bernal, Jose, and Claudia Mazo. "Transparency of Artificial Intelligence in Healthcare: Insights from Professionals in Computing and Healthcare Worldwide." Applied Sciences 12, no. 20 (2022): 10228. http://dx.doi.org/10.3390/app122010228.

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Although it is widely assumed that Artificial Intelligence (AI) will revolutionise healthcare in the near future, considerable progress must yet be made in order to gain the trust of healthcare professionals and patients. Improving AI transparency is a promising avenue for addressing such trust issues. However, transparency still lacks maturation and definitions. We seek to answer what challenges do experts and professionals in computing and healthcare identify concerning transparency of AI in healthcare? Here, we examine AI transparency in healthcare from five angles: interpretability, privac

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