Gotowe bibliografie tematyczne / AI for health

Spis treści

  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji
  6. Raporty organizacyjne

Gotowa bibliografia na temat „AI for health”

Autor: Grafiati
Data publikacji: 1 lutego 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "AI for health"

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Nelson R Saranya, Sharon. "Revolutionizing Health Records: The AI Way." International Journal of Science and Research (IJSR) 13, no. 4 (2024): 1310–13. http://dx.doi.org/10.21275/sr24417190214.

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Barassi, Veronica, and Rahi Patra. "AI Errors in Health?" Morals & Machines 2, no. 1 (2022): 34–43. http://dx.doi.org/10.5771/2747-5174-2022-1-34.

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The ever-greater use of AI-driven technologies in the health sector begs moral questions regarding what it means for algorithms to mis-understand and mis-measure human health and how as a society we are understanding AI errors in health. This article argues that AI errors in health are putting us in front of the problem that our AI technologies do not grasp the full pluriverse of human experience, and rely on data and measures that have a long history of scientific bias. However, as we shall see in this paper, contemporary public debate on the issue is very limited. Drawing on a discourse anal
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Sumit. "AI Health Care Chatbot." International Journal for Modern Trends in Science and Technology 6, no. 12 (2020): 219–24. http://dx.doi.org/10.46501/ijmtst061241.

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Healthcare bot is a technology that makes interaction between man and machine possible by using Artificial Intelligence with the support of dialog flow. Now a day people tend to seek knowledge or information from internet that concern with health through online healthcare services. To lead a good life healthcare is very much important. But it is very difficult to obtain the consultation with the doctor in case of any health issues. The basic aim of this system is to bridge the vocabulary gap between the doctors by giving self-diagnosis from the comfort of one’s place. The proposed idea is to c
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D’Alfonso, Simon. "AI in mental health." Current Opinion in Psychology 36 (December 2020): 112–17. http://dx.doi.org/10.1016/j.copsyc.2020.04.005.

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Oppermann, Ian. "Regulating AI for health." BMJ Health & Care Informatics Online 30, no. 1 (2023): e100931. http://dx.doi.org/10.1136/bmjhci-2023-100931.

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Annapurna, P. V. B. "Medicare - AI Health Diagnosis." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 19–24. https://doi.org/10.22214/ijraset.2025.69010.

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Abstract: The Medicare AI System is an intelligent healthcare assistant that utilizes React, Flask, MongoDB, Random Forest Classifier, and Raspberry Pi to provide accurate and real-time disease prediction and medical recommendations. The system is designed to assist users by allowing them to input symptoms, which are then analysed using machine learning models to predict potential diseases and suggest medications, diet plans, and preventive measures. The frontend is built using React, ensuring a responsive and user-friendly interface where users can enter symptoms and receive health insights.
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A, Arif, and Srivastava P. "Revolutionizing Eye Health: AI-Powered Diagnosis and Screening." Open Access Journal of Ophthalmology 9, no. 2 (2024): 1–6. https://doi.org/10.23880/oajo-16000328.

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Artificial intelligence (AI) has contributed to healthcare, particularly in the field of ophthalmology. This article focuses on how AI has improved detection and diagnosis of common eye diseases such as diabetic retinopathy (DR) and age-related macular degeneration (AMD). With AI-based systems, healthcare professionals can now receive more accurate diagnoses faster and create personalized treatment plans. The article also explains how AI is used to detect eye diseases. This includes collecting data, selecting components, preparing data, training models, analyzing data, developing, and refining
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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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Mehta, Mehul C., Ingrid T. Katz, and Ashish K. Jha. "Transforming Global Health with AI." New England Journal of Medicine 382, no. 9 (2020): 791–93. http://dx.doi.org/10.1056/nejmp1912079.

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KR, Prahlad. "AI Health Chatbot using ML." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33761.

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This project aims to develop a personalized and interactive healthcare chatbot leveraging natural language processing and machine learning. It offers tailored advice based on user symptoms, medical history, and preferences. Integrated with healthcare databases, it provides reliable information and services like symptom analysis, triage recommendations, medication details, and personalized health tips. Seamlessly accessing patient records and appointment schedules within existing healthcare systems ensures a cohesive user experience. The AI healthcare chatbot optimizes services by reducing comm
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Rozprawy doktorskie na temat "AI for health"

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GLORIOSO, VALERIA PAOLA. "L'universalismo incompiuto.Disuguaglianze socioeconomiche e inquità nell'accesso ai servizi sanitari in Italia." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/46373.

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Equity has long been considered an important goal in the health sector. Yet, inequalities between different social groups persist. In particular, lower-status socioeconomic groups tend to suffer higher rates of mortality and morbidity than do higher-status socioeconomic groups. Also, disadvantaged groups often use health care services less, despite generally having higher levels of need. Scholars often argue that these inequalities reflect mainly differences in constraints, rather than differences in preferences, so that they should be considered as inequities, i.e., as an instance of social i
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Schiele, Julian [Verfasser], and Jens O. [Akademischer Betreuer] Brunner. "AI-Enabled Decision Support in Health Care / Julian Schiele ; Betreuer: Jens O. Brunner." Augsburg : Universität Augsburg, 2020. http://d-nb.info/1217194029/34.

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Gozuyilmaz, Cem. "A System Approach To Occupational Health And Safety Management." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1095231/index.pdf.

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In this thesis, methods used at present in occupational health and safety management are analyzed and a model safety management system is developed. History, development and recent occupational safety regulations in the United States of America and European Union are introduced to give a sight on this subject in developed countries. The suggested model is evaluated with work accident data taken from a company and hazard and risk analysis methods are used to investigate these accidents. Preventive measures to eliminate and reduce the consequences of these accidents are recommended. Finally a
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Rahaman, Khan Md Atiqur. "Feasibility Analysis of AI based Wearable Data-driven Solution for Safety and Health in Sweden." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239442.

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This thesis investigates the prospects of AI and IoT based wearable solution in order to enhance the occupational safety and health. Thus this study contributes to find the probable use cases that can be suitable for such a technology. Later also investigation has been done to figure out how appropriate the Swedish market will be to target on. At the beginning of the thesis, it includes an overall scenario about the occupational safety/health globally as well as in Sweden. Later to improve the workplace injuries, how AI based wearable solution can be handy has been visualized. The theoretical
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Chaptoukaev, Hava. "AI for e-Health : Robust Artificial Intelligence Models for the Analysis of Wearable Medical Devices Data." Electronic Thesis or Diss., Sorbonne université, 2025. http://www.theses.fr/2025SORUS083.

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L'analyse basée sur l'intelligence artificielle (IA) des données multimodales collectées à l'aide de capteurs portables, peu coûteux et accessibles, apparaît comme une opportunité prometteuse pour démocratiser l'accès aux soins de santé. Elle faciliterait la prévention de divers problèmes de santé et réduirait la nécessité d'examens cliniques coûteux, difficilement accessibles à une grande partie de la population. Toutefois, la fiabilité et la robustesse des algorithmes d'IA, souvent négligées dans la recherche sur les soins de santé, suscitent encore des inquiétudes. D'une part, les algorithm
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Dorrikhteh, Masoud. "A Deep-Learning Approach for Marker-less Stride Parameters Analysis with Two Cameras." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42511.

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Human gait analysis is an essential indicator for physical and neuroglial health of an individual. Recent developments in deep-learning approaches to computer vision make possible new techniques for body segment and joint detection from photos and video frames. In this thesis, we propose a deep learning approach for non-invasive video-based gait analysis using two RGB cameras that would be suitable for routine gait monitoring in senior care and rehabilitation centers. Due to modularity and the low cost of implementation, it is considered an affordable solution for such centers. Furthermore, s
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Bonarrigo, Manuel. "Panoramica dell'approccio architetturale orientato ai microservizi e analisi dell'applicabilità nel contesto TraumaTracker." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16812/.

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Lo scopo di questa tesi consiste in uno studio di fattibilità dell'eventuale migrazione del progetto TraumaTracker, uno strumento informatico realizzato in collaborazione con il TraumaCenter dell'ospedale Maurizio Bufalini di Cesena, verso un approccio architetturale orientato ai microservizi. Le motivazioni che hanno portato alla considerazione di questa recente concretizzazione della service orientation derivano dalla natura di strumento medico-ospedaliero assunta dal TraumaTracker, dal quale ci si aspetta di ottenere gli stessi livelli di resilienza rispetto ai fallimenti di rete, macchine
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Silvaggi, Fabiola. "Il wellness at work come risposta ai cambiamenti della forza lavoro." Doctoral thesis, Università degli studi di Bergamo, 2017. http://hdl.handle.net/10446/77127.

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Il mio progetto di ricerca è stato incentrato su due aspetti del wellness at work: il primo inerente la relazione tra la work ability delle persone con malattie croniche e le variabili socio-economiche ad essa correlate (presentismo, assenteismo, produttività al lavoro, ecc) e il secondo relativo alla relazione tra la prevenzione primaria e le condizioni salutari dei lavoratori, al fine di rilevare quale organizzazione del lavoro delle singole imprese sia più idonea a gestire la presenza o il ritorno in attività di una forza-lavoro con problemi di salute o potenzialmente tale. Ai fini
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Franzén, Johnny. "Folkhälsovetenskap i en tid av klimatförändringar, digitalisering och orättvisa : En kartläggande studie om den artificiella intelligensens betydelse i hanteringen av klimatrelaterade folkhälsohot." Thesis, Högskolan i Skövde, Institutionen för hälsovetenskaper, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19855.

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Introduktion: Varje år dör 300 000 människor i världen på grund av klimatförändringarna och 325 miljoner påverkas allvarligt. De som i huvudsak drabbas är människor som redan är utsatta och de finns både i rika och fattiga länder. Dessa konsekvenser leder till stora sociala orättvisor mellan utvecklade länder och outvecklade men även inom nationer, därför kommer en global hälsa i en vidare mening beträffande naturkapital, humankapital och socialt kapital att krävas. Där bördorna delas och skador undviks genom mitigation, anpassning och hälsoprevention. Den pågående digitaliseringen i samhället
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Karlsson, Jennica, and Ann Charlotte Lindberg. "Hur påverkas folkhälsan av Artificiell Intelligens? : En litteraturstudie av hur hälsans sociala bestämningsfaktorer påverkas av AI inom området avsiktliga skador." Thesis, Högskolan i Skövde, Institutionen för hälsa och lärande, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17128.

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Introduktion: Befolkningens hälsa påverkas i hög grad av hur väl samhället vi lever i fungerar. Samhällen präglade av våld, krig och terror får negativa konsekvenser för människors hälsa. Artificiell Intelligens (AI) är en kraftfull teknik med stora möjligheter att lösa samhällsproblem, men forskare varnar för att AI också kan innebära nya risker. Syfte: Syftet med litteraturstudien är att belysa vilka utmaningar och möjligheter som en ökande utveckling och implementering av AI kan ha på hälsans sociala bestämningsfaktorer inom området avsiktliga skador. Metod: Enligt Denyer och Tranfields (20
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Książki na temat "AI for health"

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Lawry, Tom. AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214.

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Adirim, Terry, ed. Digital Health, AI and Generative AI in Healthcare. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83526-1.

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Aluvalu, Rajanikanth, Mayuri Mehta, and Patrick Siarry, eds. Explainable AI in Health Informatics. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3705-5.

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Yang, Hui, Robin Qiu, and Weiwei Chen, eds. AI and Analytics for Public Health. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-75166-1.

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Shaban-Nejad, Arash, Martin Michalowski, and Simone Bianco, eds. AI for Health Equity and Fairness. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63592-2.

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xuan, Chen nian. Ai ℗ʺSPA. Ke xue chu ban she, 2004.

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Little, Jean. Ai quan yang hu da quan. Wan li ji gou, wan li shu dian, 1994.

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shi, Liling shi ai guo wei sheng yun dong wei yuan hui Ban gong. Liling ai guo wei sheng zhi. s.n., 1991.

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Aloulou, Hamdi, Bessam Abdulrazak, Antoine de Marassé-Enouf, and Mounir Mokhtari, eds. Participative Urban Health and Healthy Aging in the Age of AI. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09593-1.

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Pagán, José, Mounir Mokhtari, Hamdi Aloulou, Bessam Abdulrazak, and María Fernanda Cabrera, eds. How AI Impacts Urban Living and Public Health. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32785-9.

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Części książek na temat "AI for health"

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Cantilina, Thomas J. "Health Informatics." In Digital Health, AI and Generative AI in Healthcare. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83526-1_3.

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Wickramasinghe, Nilmini. "Exploring the Potential of ChatGPT, Responsible AI, Explainable AI and Generative AI." In Digital Health. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003318538-10.

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Adirim, Terry. "Digital Health Technologies: Virtual Health and Remote Patient Monitoring." In Digital Health, AI and Generative AI in Healthcare. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83526-1_2.

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Lawry, Tom. "When AI Meets HR." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-10.

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Lawry, Tom. "Engaging Your Clinicians." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-11.

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Lawry, Tom. "Making Radiologists More Rad." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-12.

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Lawry, Tom. "Understanding and Managing the Ethics of AI." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-13.

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Lawry, Tom. "The Role of the Cloud in AI." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-14.

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Lawry, Tom. "Manage Your Data Estate Like Your Finances." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-15.

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Lawry, Tom. "The Importance of Intelligent HIT Vendors." In AI in Health. HIMSS Publishing, 2020. http://dx.doi.org/10.4324/9780429321214-16.

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Streszczenia konferencji na temat "AI for health"

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Singh, Karandeep. "Tackling the health AI paradox." In Imaging Informatics, edited by Shandong Wu. SPIE, 2025. https://doi.org/10.1117/12.3055542.

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Bhatnagar, Nachiketa, Faisal Abdullah Khan, V. Angayarkanni, J. Kalaivani, and P. Rama. "AI Enhanced Mental Health System." In 2025 3rd International Conference on Smart Systems for applications in Electrical Sciences (ICSSES). IEEE, 2025. https://doi.org/10.1109/icsses64899.2025.11009803.

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Siraskar, Warsha Prashant, Parul Dubey, Niharika Das, Pushpa Chutel, Prachi Jain, and Rahul Vinayak Bambodkar. "Enhancing Cardiovascular Health through AI-Driven Heart Disease Detection." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10738991.

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I, Shifa Fathima, Kamalesh S, and Indhumugi S. "WellSphere: AI-Driven Lifestyle Health Diagnosis." In 2025 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE). IEEE, 2025. https://doi.org/10.1109/iitcee64140.2025.10915468.

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A S, Dhanyavarthini, Nivetha S, Pushpa Dharini S, Malaiarasu G, and V. Kalaivani. "CalmSphere: An AI for Mental Health." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076380.

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R, Jayabhaduri, Aadesh Vijayaraghavan, Ajay Karthik R, Ceralaathan G, and Sai Sailesh S. "AI Powered Chatbot For Mental Health Treatment." In 2024 First International Conference on Technological Innovations and Advance Computing (TIACOMP). IEEE, 2024. http://dx.doi.org/10.1109/tiacomp64125.2024.00037.

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Prathaban, Banu Priya, R. Subash, Ashwini A, and Lakshmi G. "AI based Mental Health Assisted Chatbot System." In 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). IEEE, 2024. https://doi.org/10.1109/icpects62210.2024.10780017.

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Barkhade, Jayesh, Sahil Jagtap, Gayatri Shahare, Kamlesh Kalbande, Pooja Yerunkar, and Prasheel Thakre. "AI BOT: Mental Health Detection and Counselling." In 2024 International Conference on Big Data Analytics in Bioinformatics (DABCon). IEEE, 2024. https://doi.org/10.1109/dabcon63472.2024.10919413.

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Manoharan, Geetha, Lalit Mohan Pant, Ruchi Tewari, Swapnil Vichare, Prithu Sarkar, and Joshuva Arockia Dhanraj. "AI-Powered Chatbots for Mental Health Support." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10829185.

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Saranya, T., Subbiah S, and Dhanaseelan V. "AI Based Identification of Plant Health Issues." In 2024 9th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2024. https://doi.org/10.1109/icces63552.2024.10859404.

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Raporty organizacyjne na temat "AI for health"

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Manca, Fabio, and Diego Eslava. Digital and AI skills in health occupations. Organisation for Economic Co-Operation and Development (OECD), 2025. https://doi.org/10.1787/5fbd42ab-en.

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Smeaton, John, and Lorna Christie. AI and healthcare. Parliamentary Office of Science and Technology, 2021. http://dx.doi.org/10.58248/pn637.

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There are various applications of Artificial Intelligence (AI) in healthcare, such as helping clinicians to make decisions, monitoring patient health, and automating routine administrative tasks. This POSTnote gives an overview of these uses, and their potential impacts on the cost and quality of healthcare, and on the workforce. It summarises the challenges to wider adoption of AI in healthcare, including those relating to safety, privacy, data-sharing, trust, accountability and health inequalities. It also outlines some of the regulations relevant to AI, and how these may change. As healthca
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Juanita, Safitri, Mauridhi Hery Purnomo, and Diana Purwitasari. AI shows its worth in making sense of online health. Edited by Ria Ernunsari and Sara Phillips. Monash University, 2022. http://dx.doi.org/10.54377/3ff3-6cf7.

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Lampkin, Cheryl L. AI in Health Care: Thoughts and Opinions Among the 50+. AARP Research, 2024. http://dx.doi.org/10.26419/res.00802.001.

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Jain, Trishala. This is our future "HealQuest"- An AI Mental Health Application. Iowa State University, 2024. https://doi.org/10.31274/cc-20250502-76.

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Bagchi, Devarati, Vidya Prabhu, and Divya Sussana Patil. AI and big data analytics in health care: Opportunity or threat? World Evidence-based Healthcare Day, 2024. http://dx.doi.org/10.70253/vnhr9587.

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Rudd, Ian. Leveraging Artificial Intelligence and Robotics to Improve Mental Health. Intellectual Archive, 2022. http://dx.doi.org/10.32370/iaj.2710.

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Artificial Intelligence (AI) is one of the oldest fields of computer science used in building structures that look like human beings in terms of thinking, learning, solving problems, and decision making (Jovanovic et al., 2021). AI technologies and techniques have been in application in various aspects to aid in solving problems and performing tasks more reliably, efficiently, and effectively than what would happen without their use. These technologies have also been reshaping the health sector's field, particularly digital tools and medical robotics (Dantas & Nogaroli, 2021). The new real
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Strange, Michael. AI and the everyday political-economy of global health : a research protocol. Malmö University, 2020. http://dx.doi.org/10.24834/isbn.9789178775330.

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Pasupuleti, Murali Krishna. AI and Quantum-Nano Frontiers: Innovations in Health, Sustainability, Energy, and Security. National Education Services, 2025. https://doi.org/10.62311/nesx/rr525.

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Abstract: This research report explores transformative advancements at the intersection of Artificial Intelligence (AI), Quantum Computing, and Nanotechnology, focusing on breakthrough innovations in health, sustainability, energy, and global security. By integrating quantum algorithms, AI-driven analytics, and advanced nanomaterials, this report highlights revolutionary solutions in precision medicine, predictive diagnostics, sustainable energy storage, universal water purification, and cybersecurity. Real-world case studies and emerging technologies such as graphene-based nanomaterials, quan
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Maerz, Seraphine. Using AI for Text Analysis in R. Instats Inc., 2024. http://dx.doi.org/10.61700/ti5uexui5ilrd1663.

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This one-day workshop provides a basic introduction to using artificial intelligence for text analysis. Tailored for researchers across a variety of social and health science fields, participants will gain practical skills in building text corpuses, topic modeling, and using ChatGPT, Copilot, and other Large Language Models (LLMs) in R, while addressing ethical considerations and validation techniques for AI-driven research.
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