Top Papers: Machine Learning im Gesundheitswesen (2023)

Die 50 meistzitierten Arbeiten zu Machine Learning im Gesundheitswesen aus dem Jahr 2023 (von 6.947 insgesamt).

Machine Learning verändert das Gesundheitswesen grundlegend – von der Vorhersage von Krankheitsverläufen über die Optimierung von Behandlungspfaden bis hin zur Identifikation von Risikogruppen. Klinische Daten, Laborwerte und Bildgebungsdaten werden mit ML-Modellen ausgewertet, um Entscheidungen schneller und fundierter zu treffen. Diese Seite bündelt die relevantesten Studien und ihre Ergebnisse.

2021 2022 2023 2024

#	Paper	Zitationen
1	Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models Tiffany H. Kung, Morgan Cheatham, Arielle Medenilla et al. PLOS Digital Health	3.464
2	Large language models in medicine Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan et al. Nature Medicine	3.130
3	Revolutionizing healthcare: the role of artificial intelligence in clinical practice Shuroug A. Alowais, Sahar S. Alghamdi, Nada Alsuhebany et al. BMC Medical Education	2.699
4	MIMIC-IV, a freely accessible electronic health record dataset Alistair E. W. Johnson, Lucas Bulgarelli, Lu Shen et al. Scientific Data	2.602
5	ChatGPT: five priorities for research Eva A.M. van Dis, Johan Bollen, Willem Zuidema et al. Nature	1.761
6	Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence Vikas Hassija, Vinay Chamola, Atmesh Mahapatra et al. Cognitive Computation	1.615
7	Sparks of Artificial General Intelligence: Early experiments with GPT-4 Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan et al. arXiv (Cornell University)	1.542
8	Foundation models for generalist medical artificial intelligence Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad et al. Nature	1.481
9	Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence Sajid Ali, Tamer Abuhmed, Shaker El–Sappagh et al. Information Fusion	1.416
10	Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration Fiona Fui‐Hoon Nah, Ruilin Zheng, Jingyuan Cai et al. Journal of Information Technology Case and Application Research	1.171
11	ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations Tirth Dave, Sai Anirudh Athaluri, Satyam Singh Frontiers in Artificial Intelligence	1.158
12	Summary of ChatGPT-Related research and perspective towards the future of large language models Yiheng Liu, Tianle Han, Siyuan Ma et al. Meta-Radiology	717
13	Role of Chat GPT in Public Health Som Biswas Annals of Biomedical Engineering	661
14	ChatGPT - Reshaping medical education and clinical management Rehan Ahmed Khan, Masood Jawaid, Aymen Rehan Khan et al. Pakistan Journal of Medical Sciences	638
15	Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial Bertalan Meskó Journal of Medical Internet Research	632
16	Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model Douglas B. Johnson, Rachel Goodman, James R. Patrinely et al. Research Square	589
17	Algorithmic fairness in artificial intelligence for medicine and healthcare Richard J. Chen, Judy J. Wang, Drew F. K. Williamson et al. Nature Biomedical Engineering	547
18	Effective Heart Disease Prediction Using Machine Learning Techniques Chintan Bhatt, P. V. Patel, Tarang Ghetia et al. Algorithms	509
19	Utility of ChatGPT in Clinical Practice Jialin Liu, Changyu Wang, Siru Liu Journal of Medical Internet Research	501
20	Appropriateness of Cardiovascular Disease Prevention Recommendations Obtained From a Popular Online Chat-Based Artificial Intelligence Model Ashish Sarraju, Dennis Bruemmer, Erik H. Van Iterson et al. JAMA	469
21	Health system-scale language models are all-purpose prediction engines Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian et al. Nature	432
22	Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine Stefan Harrer EBioMedicine	430
23	Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study Travis Zack, Eric Lehman, Mirac Süzgün et al. The Lancet Digital Health	427
24	Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge Zahir Kanjee, Byron Crowe, Adam Rodman JAMA	414
25	SAITS: Self-attention-based imputation for time series Wenjie Du, David Côté, Yan Liu Expert Systems with Applications	410
26	Using AI-generated suggestions from ChatGPT to optimize clinical decision support Siru Liu, Aileen P. Wright, Barron L. Patterson et al. Journal of the American Medical Informatics Association	393
27	Creation and Adoption of Large Language Models in Medicine Nigam H. Shah, David A. Entwistle, Michael A. Pfeffer JAMA	391
28	A systematic review of Explainable Artificial Intelligence models and applications: Recent developments and future trends A. Saranya, R. Subhashini Decision Analytics Journal	383
29	Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study Arya Rao, Michael Pang, John Kim et al. Journal of Medical Internet Research	380
30	Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT Augustin Lecler, Loïc Duron, Philippe Soyer Diagnostic and Interventional Imaging	373
31	Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges Peng Zhang, Maged N. Kamel Boulos Future Internet	366
32	A study of generative large language model for medical research and healthcare Peng Cheng, Xi Yang, Aokun Chen et al. npj Digital Medicine	360
33	Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints: A Pilot Study Takanobu Hirosawa, Yukinori Harada, Masashi Yokose et al. International Journal of Environmental Research and Public Health	357
34	Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review Elias Hossain, Rajib Rana, Niall Higgins et al. Computers in Biology and Medicine	355
35	Evaluating large language models on medical evidence summarization Liyan Tang, Zhaoyi Sun, Betina Idnay et al. npj Digital Medicine	349
36	Opportunities and challenges for ChatGPT and large language models in biomedicine and health Shubo Tian, Qiao Jin, Lana Yeganova et al. Briefings in Bioinformatics	335
37	TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation Keqin Bao, Jizhi Zhang, Yang Zhang et al. —	334
38	Towards Expert-Level Medical Question Answering with Large Language Models Karan Singhal, Tao Tu, Juraj Gottweis et al. arXiv (Cornell University)	333
39	What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine Jakub Kufel, Katarzyna Bargieł-Łączek, Szymon Kocot et al. Diagnostics	330
40	Ensemble Learning for Disease Prediction: A Review Palak Mahajan, Shahadat Uddin, Farshid Hajati et al. Healthcare	329
41	SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models Potsawee Manakul, Adian Liusie, Mark Gales —	328
42	Large language models in health care: Development, applications, and challenges Rui Yang, Ting Fang Tan, Wei Lu et al. Health care science	327
43	Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard Zhi Wei Lim, Krithi Pushpanathan, Samantha Min Er Yew et al. EBioMedicine	305
44	A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories Davide Placido, Bo Yuan, Jessica Xin Hjaltelin et al. Nature Medicine	305
45	A survey of GPT-3 family large language models including ChatGPT and GPT-4 Katikapalli Subramanyam Kalyan Natural Language Processing Journal	304
46	ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model Hanyao Huang, Ou Zheng, Dongdong Wang et al. International Journal of Oral Science	300
47	A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare Molla Imaduddin Ahmed, Brendan Spooner, John Isherwood et al. Cureus	299
48	A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges Qi An, Saifur Rahman, Jingwen Zhou et al. Sensors	298
49	A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics Hong-Yu Zhou, Yizhou Yu, Chengdi Wang et al. Nature Biomedical Engineering	289
50	Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information Skyler B. Johnson, Andy J. King, Echo L. Warner et al. JNCI Cancer Spectrum	288

Top Papers: Machine Learning im Gesundheitswesen (2023)

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