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Journal articles on the topic 'AI in Medicine'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Adinolfi, Gianmarco. "AI in Medicine." Pleven Blog&Journal, no. 4 (March 31, 2025): 9–17. https://doi.org/10.5281/zenodo.15308620.

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This academic article was written by a medical student and published in <em>Pleven Blog&Journal</em>, Issue 4, released on March 31, 2025. The journal is an academic <strong>student-led</strong> platform, dedicated to promoting scientific activity, collaboration, and intellectual engagement among peers in the medical and academic communities. It serves as a space to support early scientific contributions while encouraging the growth of academic interest within the faculty.

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Pakdemirli, Ahu, and Asim Leblebici. "AI in Medicine versus AI in Prehospital." Medicine Science | International Medical Journal 9, no. 2 (2020): 293. http://dx.doi.org/10.5455/medscience.2020.09.9186.

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Molchanova, Irma I., and Nadezhda V. Sokolova. "Features of translation of medical instructions from English and French languages into Russian (Pharmacological discourse)." Revista Amazonia Investiga 9, no. 26 (2020): 52–59. http://dx.doi.org/10.34069/ai/2020.26.02.5.

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The purpose of the study is to reveal difficulties in translating instructions on the usage of medicines from English and French into Russian. Translation of medical instructions is a private form of medical translation that is in high demand. Each medicine should have a detailed description in Russian. With this document, a manufacturer guarantees to patient that subject to the prescribed standards, medicine will provide a certain effect that it is safe for life and health. The instruction is a kind of memo for a patient and a guarantee of the correctness of taking medicine. The authors of th

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Grosek, Štefan, Stjepan Štivić, Ana Borovečki, et al. "Ethical attitudes and perspectives of AI use in medicine between Croatian and Slovenian faculty members of school of medicine: Cross-sectional study." PLOS ONE 19, no. 12 (2024): e0310599. https://doi.org/10.1371/journal.pone.0310599.

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Background Artificial intelligence (AI) is present in preclinical, clinical and research work, in various branches of medicine. Researchers and teachers at school of medicines may have different ethical attitudes and perspectives about the implementation of AI systems in medicine. Methods We conducted an online survey among researchers and teachers (RTs) at the departments and institutes of two Slovenian and four Croatian Schools of Medicine. Results The sample included 165 and 214 researchers and teachers in Slovenia and Croatia, respectively. The sample of respondents in Slovenia and Croatia

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Filetti, Marco, Manuela Petti, and Lorenzo Farina. "Precision medicine: Beyond AI." Computer Methods and Programs in Biomedicine Update 5 (2024): 100157. http://dx.doi.org/10.1016/j.cmpbup.2024.100157.

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Looi, Mun-Keat. "Can AI teach medicine?" BMJ 389 (May 14, 2025): r822. https://doi.org/10.1136/bmj.r822.

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Park, Seong Ho, Kyung-Hyun Do, Sungwon Kim, Joo Hyun Park, and Young-Suk Lim. "What should medical students know about artificial intelligence in medicine?" Journal of Educational Evaluation for Health Professions 16 (July 3, 2019): 18. http://dx.doi.org/10.3352/jeehp.2019.16.18.

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Artificial intelligence (AI) is expected to affect various fields of medicine substantially and has the potential to improve many aspects of healthcare. However, AI has been creating much hype, too. In applying AI technology to patients, medical professionals should be able to resolve any anxiety, confusion, and questions that patients and the public may have. Also, they are responsible for ensuring that AI becomes a technology beneficial for patient care. These make the acquisition of sound knowledge and experience about AI a task of high importance for medical students. Preparing for AI does

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albarracíín, pilar. "Ai, Ai, Ai." Gastronomica 8, no. 4 (2008): 122. http://dx.doi.org/10.1525/gfc.2008.8.4.122.

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Varun, Ahuja. "Artificial Intelligence (AI) in Drug Discovery and Medicine." Journal of Clinical Cases & Reports 2, no. 3 (2019): 76–80. http://dx.doi.org/10.46619/joccr.2019.2-1043.

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Artificial intelligence (AI) is a branch of computer science that deals with the development of algorithms that seek to simulate human intelligence. The phrase “artificial intelligence” was likely coined during a conference at Dartmouth College in 1956. The earliest work of medical AI dates back to the early 1970s. Over years, AI has found implications in various fields. In this article, we summarize its applications in drug discovery and medicine.

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Pokataev, Pavlo, Oleh Bodnarchuk, Tetiana Hryshyna, Vladyslav Korolkov, and Yurii Demianchuk. "Advertising of medicines in Ukraine: An ethical and legal view." Revista Amazonia Investiga 12, no. 64 (2023): 348–60. http://dx.doi.org/10.34069/ai/2023.64.04.37.

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The modern course of Ukraine towards economic and political and legal rapprochement with European states involves the adoption of uniform rules in the field of healthcare. The objective of this article is to examine the ethical and legal aspects of advertising medicines in the context of Ukraine's alignment with European states and the adoption of uniform healthcare rules. The article employs a dialectical method to explore the correlation between ethical and legal components in medicine advertising. By analyzing domestic normative and legislative acts, there was establish methodological featu

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Rajpurkar, Pranav, Emma Chen, Oishi Banerjee, and Eric J. Topol. "AI in health and medicine." Nature Medicine 28, no. 1 (2022): 31–38. http://dx.doi.org/10.1038/s41591-021-01614-0.

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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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Rosales, Raymond L. "Editorial: Precision Medicine Meets AI." Journal of Medicine, University of Santo Tomas 8, no. 2 (2024): 1403–4. http://dx.doi.org/10.35460/2546-1621.2024-0185.

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There are rapid advancements in AI-driven diagnostics and wearable technologies, which are enabling early disease prediction, especially in conditions like Parkinson's disease. Precision medicine, underpinned by molecular biology and genomic data, allows clinicians to tailor treatment based on patient phenotypes, significantly enhancing personalized healthcare. AI complements this by processing vast datasets, from health records to biomarker evaluations, supporting more precise diagnostics and treatment recommendations.

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Thawillarp, Supharerk. "Generative AI, ChatGPT and Medicine." PSU Medical Journal 3, no. 2 (2023): 63–67. http://dx.doi.org/10.31584/psumj.2023259047.

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Moosa, Yousuf, Muhammad Hamza Khan Alizai, Araib Tahir, Sehrish Zia, Syeda Sadia, and Muhammad Taimor Fareed. "Artificial Intelligence in oral medicine." International journal of health sciences 7, S1 (2023): 1476–88. http://dx.doi.org/10.53730/ijhs.v7ns1.14369.

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Artificial Intelligence (AI) has revolutionized various fields, including healthcare, by enhancing diagnostic accuracy, treatment planning, and patient care. In the field of oral medicine, AI has emerged as a powerful tool with the potential to transform dental practice and improve patient outcomes. This study aims to investigate the perceptions and attitudes of dentists towards the integration of AI in oral medicine. A sample size of 200 dentists was recruited for this study. A structured questionnaire was developed to gather data on their knowledge, experience, and opinions regarding AI in o

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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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Nabila, Ounasser, Rhanoui Maryem, Mikram Mounia, and El Asri Bouchra. "Abrief on artificial intelligence in medicine." International Journal of Advances in Applied Sciences (IJAAS) 13, no. 4 (2024): 1055–64. https://doi.org/10.11591/ijaas.v13.i4.pp1055-1064.

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This review explores the transformative impact of artificial intelligence (AI) in medicine. It discusses the benefits of AI, its core technologies, integration pro cesses, and diverse applications. AI enhances diagnostics, personalizes treat ments, and optimizes healthcare operations. Machine learning and deep learning are key AI technologies, while explainable AI ensures transparency. The review emphasizes the integration journey and highlights AI applications, from image diagnosis to telemedicine. Ethical concerns, data privacy, regulations, and algo rithmic bias are challenges. The future p

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Banerjee, Amitav. "Artificial Intelligence beyond Chess: Opportunities for Medicine, Public Health, and Social Medicine." Journal of Comprehensive Health 8, no. 1 (2021): 6–8. http://dx.doi.org/10.53553/jch.v08i01.002.

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History was created in 1997 when Deep Blue, an Artificial Intelligence (AI) enabled chess engine, beat the world chess champion. Since then AI and machine learning are being increasingly used in other fields including health care to perform complex tasks. The present commentary compares chess and medicine and how lessons learnt from the application of AI in chess leading to â€œadvanced chessâ€ can be used to develop AI enabled â€œadvanced medicine.â€ It supports the proposition that while at present it may appear that advances in medical technology are putting a strain on the doctor-patient

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Wang, Renjie, Wei Pan, Lei Jin, et al. "Artificial intelligence in reproductive medicine." Reproduction 158, no. 4 (2019): R139—R154. http://dx.doi.org/10.1530/rep-18-0523.

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Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine

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Ounasser, Nabila, Maryem Rhanoui, Mounia Mikram, and Bouchra El Asri. "A brief on artificial intelligence in medicine." International Journal of Advances in Applied Sciences 13, no. 4 (2024): 1055. http://dx.doi.org/10.11591/ijaas.v13.i4.pp1055-1064.

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This review explores the transformative impact of artificial intelligence (AI) in medicine. It discusses the benefits of AI, its core technologies, integration processes, and diverse applications. AI enhances diagnostics, personalizes treatments, and optimizes healthcare operations. Machine learning and deep learning are key AI technologies, while explainable AI ensures transparency. The review emphasizes the integration journey and highlights AI applications, from image diagnosis to telemedicine. Ethical concerns, data privacy, regulations, and algorithmic bias are challenges. The future prom

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S R,, Dr Shankar Gowda. "MediBot: Revolutionizing Healthcare with an Intelligent Online Medicine Ordering Assistant." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31115.

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The integration of AI (Artificial Intelligence) in healthcare has witnessed significant advancements, contributing to improves patient experiences. This study introduces an AI chatbot designed specifically for medicine ordering, aimed at enhancing accessibility, efficiency, and user satisfaction in the healthcare sector. The chatbot uses Natural Language Processing (NLP) to understand and respond to user needs related to medicine orders. By using a traditional relational database of pharmaceutical information, the chatbot provides accurate details on various available medicines. The chatbot of

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Koshechkin, K. A. "Regulation of artificial intelligence in medicine." Patient-Oriented Medicine and Pharmacy 1, no. 1 (2023): 32–40. http://dx.doi.org/10.37489/2949-1924-0005.

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A study on the regulation of artificial intelligence (AI) in healthcare, includes a brief overview of the current state of use of AI in healthcare and its potential benefits and risks. The article summarizes the current regulations that exist for AI in healthcare, including any relevant laws, guidelines, and best practices, including information on regulatory bodies such as the FDA and HIPAA. The ethical considerations arising from the use of AI in healthcare, such as patient confidentiality and data security, bias in algorithms, and transparency in decision making, are given. Examples of AI i

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Rimkutė, Deimantė. "AI and Liability in Medicine: The Case of Assistive-Diagnostic AI." Baltic Journal of Law & Politics 16, no. 2 (2024): 64–81. http://dx.doi.org/10.2478/bjlp-2023-0013.

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Abstract As the prevalence of assistive-diagnostic artificial intelligence (AI) grows, so too will the legal controversies surrounding its use continue to grow. Consequently, determining liability in cases where patients experience harm due to the use of assistive-diagnostic AI in personal healthcare services requires a re-evaluation of existing civil liability regulations. This article proposes a framework for addressing liability in these situations by exploring medical malpractice, organisational negligence by healthcare institutions, and producer liability.

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G Brown, David, and Frank W Samuelson. "Humble AI for 22nd century medicine." MOJ Applied Bionics and Biomechanics 8, no. 1 (2024): 50–54. http://dx.doi.org/10.15406/mojabb.2024.08.00207.

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Artificial intelligence (AI) is playing an increasingly important role in medicine. We examine the current trends in the evolution of this role and attempt to understand how it may develop over the next two hundred years, as the very nature of human existence may be altered. We are concerned with weaknesses in the AI development and deployment processes, in particular with lapses in the use of AI evaluation methodology and in the tendency of both humans and AI systems to accept unquestioningly the conclusions reached by such systems. We posit the need for a “humble” AI aware of its own limitat

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Feng, Chuwen, Shuoyan Zhou, Yuanyuan Qu, et al. "Overview of Artificial Intelligence Applications in Chinese Medicine Therapy." Evidence-Based Complementary and Alternative Medicine 2021 (March 17, 2021): 1–6. http://dx.doi.org/10.1155/2021/6678958.

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To evaluate the importance of AI technologies in modernizing traditional Chinese medicine (TCM) therapy, this article presents the systematic review of the relevant literature and explains the beneficial effects of AI technology on the TCM treatment outcomes from the experience of famous and veteran Chinese medicines, including acupuncture, Tui Na massage, and Qigong practitioners. This study also focuses on the urgent necessity to apply AI technologies to develop therapeutic models on the theme “treating the disease before it happens.” Furthermore, the study also discusses the major bottlenec

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Goutham, Bilakanti. "AI-Powered Precision Medicine Transforming Personalized Healthcare." International Journal of Leading Research Publication 4, no. 10 (2023): 1–12. https://doi.org/10.5281/zenodo.15196949.

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AI is redefining precision medicine from vast amounts of genetic, clinical, and patient data to provide personalized healthcare approaches. AI-powered genetically diverse models examine genetic variations, forecast patient response to treatment, and optimize therapy options per person. Machine learning and deep learning technologies facilitate the development of drugs by speeding up biomarker identification and minimizing trial-and-error for pharmaceutical development. AI helps in the identification of disease pattern, allowing for early diagnosis and preventive treatment. AI-based application

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Ryazanova, Svetlana V., Vladimir P. Mazaev, and Artem A. Komkov. "New trends for artificial intelligence development in medicine." CardioSomatics 12, no. 4 (2021): 227–33. http://dx.doi.org/10.17816/22217185.2021.4.201264.

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The article discusses the modern aspects of the use of artificial intelligence (AI) in medicine, the use of AI technologies in Russia and abroad. The article describes the limitations of the use of AI in various fields of medicine, discusses possible solutions, and develops electronic devices for remote and independent monitoring. The problems of information security and ethical issues of AI application are presented with the arguments of experts and expert organizations in AI issues, as well as the prospects for development and possible consequences of AI implementation. The possibilities of

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Brass, Steven, Donald Larsen, Deeksha Panuganti, Noorafsha Khan, and Vijay Khatri. "Artificial Intelligence in Healthcare: The Revolutionization of Medicine." Physician Leadership Journal 11, no. 3 (2024): 30–35. http://dx.doi.org/10.55834/plj.1825928101.

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Artificial intelligence (AI) is becoming a significant part of healthcare, with the potential to alter the landscape of medicine as we know it. The primary objective of this review is to provide definitions of crucial AI terminology and explore how AI is revolutionizing aspects of healthcare that encompass diagnosis, clinical operations, and treatment. The authors describe a framework to help leaders facilitate the selection and deployment of AI in healthcare. They also discuss the potential challenges of AI, including the regulatory angle, data bias, data accuracy, cost of AI, and how AI can

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Boychenko, O. M., and T. D. Bublii. "THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN MEDICINE." Актуальні проблеми сучасної медицини: Вісник Української медичної стоматологічної академії 24, no. 3 (2024): 137–39. http://dx.doi.org/10.31718/2077-1096.24.3.137.

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This article analyzes the prospects for using artificial intelligence (AI) in the medical field. It highlights that AI has already become an integral part of modern life and is actively utilized in various countries, particularly in diagnosis, treatment, and disease prognosis. AI enhances diagnostic accuracy, accelerates treatment processes, and optimizes medical resources significantly. Internationally, AI-based solutions are already widely implemented in countries like the USA, Japan, and China to improve healthcare services. These technologies allow doctors to process large amounts of data

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Kundu, Shinjini. "AI in medicine must be explainable." Nature Medicine 27, no. 8 (2021): 1328. http://dx.doi.org/10.1038/s41591-021-01461-z.

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Furukawa, Toshiyuki. "AI in medicine: A Japanese perspective." AI & Society 4, no. 3 (1990): 196–213. http://dx.doi.org/10.1007/bf01889940.

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Varlamov, Oleg O., Dmitry A. Chuvikov, Larisa E. Adamova, Maxim A. Petrov, Irina K. Zabolotskaya, and Tatyana N. Zhilina. "Logical, Philosophical and Ethical Aspects of AI in Medicine." International Journal of Machine Learning and Computing 9, no. 6 (2019): 868–73. http://dx.doi.org/10.18178/ijmlc.2019.9.6.885.

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Suryawanshi, Vishal Bhalchandra, and Shivangi Valand. "Personalized Medicine: AI-driven recommendations based on patient history." International Journal of Research Publication and Reviews 6, no. 3 (2025): 6334–39. https://doi.org/10.55248/gengpi.6.0325.1296.

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Savulescu, Julian, Alberto Giubilini, Robert Vandersluis, and Abhishek Mishra. "Ethics of artificial intelligence in medicine." Singapore Medical Journal 65, no. 3 (2024): 150–58. http://dx.doi.org/10.4103/singaporemedj.smj-2023-279.

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Abstract This article reviews the main ethical issues that arise from the use of artificial intelligence (AI) technologies in medicine. Issues around trust, responsibility, risks of discrimination, privacy, autonomy, and potential benefits and harms are assessed. For better or worse, AI is a promising technology that can revolutionise healthcare delivery. It is up to us to make AI a tool for the good by ensuring that ethical oversight accompanies the design, development and implementation of AI technology in clinical practice.

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Lee, Benjamin, and Christopher Peterson. "Machine learning and medicine- a brief introduction." Southwest Respiratory and Critical Care Chronicles 10, no. 45 (2022): 28–36. http://dx.doi.org/10.12746/swrccc.v10i45.1043.

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Artificial Intelligence (AI) and Machine Learning (ML) have advanced rapidly in recent years and now have the potential to change medicine. This review serves as an introduction to AI and the potential it has to change medicine. Specific examples of past milestones particularly in the domain of critical care are presented, including algorithms that have been developed that can interpret chest x-rays or predict clinical outcomes such as extubation failure or ICU mortality. Included is a brief general discussion of what AI is, how it is made, and how physicians will be involved with it. Argument

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Anjankar, Ashish Prakash, Roshan Kumar Jha, and Sandip Lambe. "Implementation of Artificial Intelligence in Laboratory Medicine." Journal of Datta Meghe Institute of Medical Sciences University 18, no. 4 (2023): 598–601. http://dx.doi.org/10.4103/jdmimsu.jdmimsu_486_22.

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Abstract Introduction: In advancing health care, the evolution of laboratory medicine is necessary to overcome the need for accurate, readily available, and relative data within the appropriate time window; we see artificial intelligence (AI) in laboratory medicine. The introduction of AI in the health-care sector has been believed as the practice of composite software and algorithms to compete with human intelligence in analysis, diagnosis, and research. Materials and Methods: A Google Form-based survey study on the use of AI in the laboratory setting was planned stepwise independently. First

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Debashish, Padhi. "Research of Artificial Intelligence in Medicine." International Journal of Innovative Science and Research Technology 7, no. 9 (2022): 60–65. https://doi.org/10.5281/zenodo.7089672.

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AI is transforming the world in every walk of life. It is collection of technologies that in future will probably rule the entire world. AI is a technology that thinks like human, learns like human but performs like super-human. In this paper, we will discuss about the application of AI in healthcare industry and all the pros and cons it is having, starting from decision making to integrating information, analysing data and use of its own results to improve itself. The technologies like Magnetic Resonance Imaging (MRI), Computed Tomography Scan (CT scan), are a part of AI that’s been wid

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Rao, J. Vijay. "Uses of Artificial Intelligence in Medicine." Telangana Journal of IMA 4, no. 2 (2024): 79–84. https://doi.org/10.4103/tjima.tjima_18_24.

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Today, everybody thinks that artificial intelligence (AI) is going to take over humankind. AI promises to revolutionize medicine, giving us a better understanding of health and diseases and the ability to make more decisions based on data. AI is a new technical discipline that uses computer technology to research and develop the theory, method, technique, and application system for the simulation, extension, and expansion of human intelligence. With the assistance of new AI technology, the traditional medical environment has changed a lot. For example, a patient’s diagnosis based on radiologic

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Jan, Tashfeen Alam, and Shumaila Naz. "Artificial Intelligence in Medicine: Transforming The Future of Healthcare." Life and Science 6, no. 2 (2025): 08. https://doi.org/10.37185/lns.1.1.904.

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The rate of development in artificial intelligence (AI) technologies has brought revolutionary transformationsacross the healthcare sector. The advancements especially impacted the manner in which the diagnosis,treatment, and management of diseases are undertaken with a growing emphasis laid on optimizing clinicalworkflow and patient care. Machine learning (ML) and deep learning (DL) technologies have proved invaluablefor the analysis of complex datasets, supporting early diagnosis and optimizing treatment protocols. AIshowcased tremendous promise in a plethora of applications, such as the acc

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Salomon, Izere, and Sibomana Olivier. "Artificial intelligence in medicine: advantages and disadvantages for today and the future." International Journal of Surgery Open 62, no. 4 (2024): 471–73. http://dx.doi.org/10.1097/io9.0000000000000133.

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The term ‘artificial intelligence’ (AI) is used to describe the application of computers and technology to mimic human problem solving and creativity. The possibility of AI in medicine is rapidly evolving and its utility in clinical practice may soon become commonplace. The application of AI in medicine has been considered an opportunity to advance medicine as it helps to store, analyze, and interpret large amounts of data and lead to increased diagnostic accuracy, speed, and optimize treatment strategies. On the other hand, many physicians are concerned that AI will replace medical profession

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Awwalu, Jamilu, Ali Garba Garba, Anahita Ghazvini, and Rose Atuah. "Artificial Intelligence in Personalized Medicine Application of AI Algorithms in Solving Personalized Medicine Problems." International Journal of Computer Theory and Engineering 7, no. 6 (2015): 439–43. http://dx.doi.org/10.7763/ijcte.2015.v7.999.

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Ruan, Chenglu, Yirong Zhu, and Jianying Xiong. "Applications and Prospects of Artificial Intelligence in Oral Medicine." Industry Science and Engineering 1, no. 2 (2024): 11–15. http://dx.doi.org/10.62381/i245203.

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In the field of dental medicine, there is an increasing exploration of the application of Artificial Intelligence (AI) to enhance the efficiency and accuracy of diagnosing, treating, and preventing oral diseases. This paper primarily investigates the current applications and future prospects of AI in the realm of dental medicine. Its purpose is to delve into the multifaceted utilization of AI in dentistry, spanning dental imaging, macrobiotics, genomics research, treatment planning, and patient management. By depicting AI applications in these domains, the article underscores its potential adv

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Jayesh, Patil* Harish Patil Ashish Panpatil Harshita Chordiya Rashmi Deore Sarode Sanskruti. "Advancements And Challenges In The Integration Of Artificial Intelligence With Herbal Medicine Research." International Journal in Pharmaceutical Sciences 2, no. 4 (2024): 973–84. https://doi.org/10.5281/zenodo.11060057.

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The convergence of artificial intelligence (AI) and herbal medicine research presents a promising avenue for accelerating drug discovery, personalized medicine, and healthcare innovation. This review paper explores the current landscape of AI-driven approaches in herbal medicine research, focusing on the application of machine learning, data mining, and natural language processing techniques. Additionally, it discusses the challenges and opportunities associated with integrating AI into herbal medicine, including data quality, interpretability, regulatory considerations, and the ethical implic

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A.S.Hovan, George, and George A.Shaji. "From Pulse to Prescription: Exploring the Rise of AI in Medicine and Its Implications." Partners Universal International Innovation Journal (PUIIJ) 01, no. 06 (2023): 38–54. https://doi.org/10.5281/zenodo.10290649.

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The practice of medicine is undergoing a significant transformation with the emergence of artificial intelligence (AI) and medical automation. Historically, medicine was highly personal, with doctors using interpersonal skills to diagnose patients. Today, over 70% of doctors rely primarily on medical tests to prescribe treatment. As AI systems analyze big data and provide diagnostic and prescription recommendations, medicine may become more efficient yet less humane. This paper explores the implications of increasing AI automation in medicine for doctors, patients, and healthcare overall.&nbsp

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Islam, Md Maruful. "Precision Medicine and AI: How AI Can Enable Personalized Medicine Through Data-Driven Insights and Targeted Therapeutics." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 11 (2023): 1267–76. https://doi.org/10.17762/ijritcc.v11i11.11359.

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Whereas traditional medicine has taken a one-size-fits-all approach, precision medicine represents a paradigm shift towards individualized care by integrating information on a patient’s genes, environment, and lifestyle for management purposes. The realization of this vision can become a reality and a key player in this process is represented by Artificial Intelligence (AI), which can turn medical data into meaningful actions. AI technologies are disrupting many aspects of personalized medicine, including predictive analytics, patient or population surveillance, and targeted therapeutics, and

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Chioma Anthonia Okolo, Tolulope Olorunsogo, and Oloruntoba Babawarun. "A comprehensive review of AI applications in personalized medicine." International Journal of Science and Research Archive 11, no. 1 (2024): 2544–49. http://dx.doi.org/10.30574/ijsra.2024.11.1.0338.

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Personalized medicine, propelled by advances in genomic and molecular understanding, is undergoing a transformative paradigm shift, and artificial intelligence (AI) is emerging as a pivotal catalyst in this evolution. This comprehensive review explores the intersection of AI and personalized medicine, aiming to provide a holistic overview of the current landscape, challenges, and future directions. The review delves into AI applications across key domains, including genomic medicine, disease diagnosis, risk prediction, patient stratification, and clinical trials. Special attention is given to

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Goel, Rajeev. "Artificial intelligence in medicine: its working, potentials and challenges." International Journal of Advances in Medicine 10, no. 1 (2022): 108. http://dx.doi.org/10.18203/2349-3933.ijam20223412.

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Artificial intelligence (AI) is the science and engineering of making intelligent machines to think and learn. The interest and involvement of AI in health care has expanded fast during the last decade. The use of AI based technologies has been integrated into medicine to raise the standard of patient care by accelerating processes and achieving greater accuracy in different clinical settings. The patient’s electronic records, pathology slides and different radiological images are nowadays assessed by AI technologies such as machine learning (ML) and deep learning (DL). This, in turn, has aide

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K.U, Bhavishya, and Akshatha CH. "Artificial Intelligence in Medicine: A Paradigm Shift." International Research Journal of Computer Science 12, no. 02 (2025): 79–83. https://doi.org/10.26562/irjcs.2025.v1202.02.

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Artificial Intelligence (AI) has the potential to revolutionize the field of medicine. This paper explores the various applications of AI in healthcare, including medical imaging, drug discovery, personalized medicine, predictive analytics, and robotic surgery. We discuss the advantages of AI, such as improved accuracy, efficiency, and accessibility. However, we also acknowledge the challenges, including data privacy, algorithm bias, and ethical considerations. Despite these challenges, the future of AI in medicine is promising, with potential for further advancements in diagnosis, treatment,

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PremaLatha, V., Anguraj Dinesh Kumar, and Nikhat Parveen. "Revolutionizing medicine: the role of AI in healthcare." Edu - Tech Enterprise 3 (April 15, 2025): 25. https://doi.org/10.71459/edutech202525.

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Artificial Intelligence (AI) is transforming the healthcare sector, introducing revolutionary advancements that redefine patient care and medical practices. From diagnostics to treatment planning, AI-powered tools enhance accuracy, efficiency, and accessibility. Machine learning algorithms can analyze complex medical data, identifying patterns and predicting outcomes that aid in early disease detection. AI-driven robotic systems support precision surgeries, while natural language processing facilitates seamless medical record management. Moreover, AI-enabled virtual health assistants and chatb

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Sitarek, Gracjan, and Marta Żerek. "Artificial Intelligence in Emergency Medicine: A Literature Review." Quality in Sport 33 (November 17, 2024): 55839. http://dx.doi.org/10.12775/qs.2024.33.55839.

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IntroductionArtificial intelligence (AI) is rapidly transforming medical fields, particularly emergency medicine (EM), where timely decision-making is crucial. AI offers potential benefits in diagnostic accuracy, patient care optimization, and workflow efficiency within emergency departments (EDs). Purpose of WorkThis review aims to synthesize recent advancements in AI applications within emergency medicine, focusing on diagnostic support, patient triage, clinical decision support systems (CDSS), and workflow optimization. Additionally, we highlight the potential benefits, challenges, and futu

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