Top Papers: Machine Learning im Gesundheitswesen (2023)

Die 50 meistzitierten Arbeiten zu Machine Learning im Gesundheitswesen aus dem Jahr 2023 (von 6.593 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	3.432
2	Large language models in medicine Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan et al. Nature Medicine	3.064
3	Revolutionizing healthcare: the role of artificial intelligence in clinical practice Shuroug A. Alowais, Sahar S. Alghamdi, Nada Alsuhebany et al. BMC Medical Education	2.652
4	MIMIC-IV, a freely accessible electronic health record dataset Alistair E. W. Johnson, Lucas Bulgarelli, Lu Shen et al. Scientific Data	2.546
5	ChatGPT: five priorities for research Eva A.M. van Dis, Johan Bollen, Willem Zuidema et al. Nature	1.751
6	Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence Vikas Hassija, Vinay Chamola, Atmesh Mahapatra et al. Cognitive Computation	1.551
7	Sparks of Artificial General Intelligence: Early experiments with GPT-4 Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan et al. arXiv (Cornell University)	1.535
8	Foundation models for generalist medical artificial intelligence Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad et al. Nature	1.452
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	1.380
10	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	1.148
11	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	1.147
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	708
13	Role of Chat GPT in Public Health Som Biswas Annals of Biomedical Engineering	657
14	ChatGPT - Reshaping medical education and clinical management Rehan Ahmed Khan, Masood Jawaid, Aymen Rehan Khan et al. Pakistan Journal of Medical Sciences	632
15	Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial Bertalan Meskó Journal of Medical Internet Research	624
16	Algorithmic fairness in artificial intelligence for medicine and healthcare Richard J. Chen, Judy J. Wang, Drew F. K. Williamson et al. Nature Biomedical Engineering	529
17	Effective Heart Disease Prediction Using Machine Learning Techniques Chintan Bhatt, P. V. Patel, Tarang Ghetia et al. Algorithms	500
18	Utility of ChatGPT in Clinical Practice Jialin Liu, Changyu Wang, Siru Liu Journal of Medical Internet Research	494
19	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	466
20	Health system-scale language models are all-purpose prediction engines Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian et al. Nature	427
21	Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine Stefan Harrer EBioMedicine	426
22	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	421
23	Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge Zahir Kanjee, Byron Crowe, Adam Rodman JAMA	409
24	SAITS: Self-attention-based imputation for time series Wenjie Du, David Côté, Yan Liu Expert Systems with Applications	396
25	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	387
26	Creation and Adoption of Large Language Models in Medicine Nigam H. Shah, David A. Entwistle, Michael A. Pfeffer JAMA	386
27	A systematic review of Explainable Artificial Intelligence models and applications: Recent developments and future trends A. Saranya, R. Subhashini Decision Analytics Journal	373
28	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	373
29	Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT Augustin Lecler, Loïc Duron, Philippe Soyer Diagnostic and Interventional Imaging	370
30	Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges Peng Zhang, Maged N. Kamel Boulos Future Internet	360
31	A study of generative large language model for medical research and healthcare Peng Cheng, Xi Yang, Aokun Chen et al. npj Digital Medicine	353
32	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	353
33	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	352
34	Evaluating large language models on medical evidence summarization Liyan Tang, Zhaoyi Sun, Betina Idnay et al. npj Digital Medicine	345
35	Towards Expert-Level Medical Question Answering with Large Language Models Karan Singhal, Tao Tu, Juraj Gottweis et al. arXiv (Cornell University)	333
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	328
37	Ensemble Learning for Disease Prediction: A Review Palak Mahajan, Shahadat Uddin, Farshid Hajati et al. Healthcare	323
38	Large language models in health care: Development, applications, and challenges Rui Yang, Ting Fang Tan, Wei Lu et al. Health care science	321
39	TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation Keqin Bao, Jizhi Zhang, Yang Zhang et al. —	319
40	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	318
41	SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models Potsawee Manakul, Adian Liusie, Mark Gales —	312
42	ChatGPT: Is this version good for healthcare and research? Raju Vaishya, Anoop Misra, Abhishek Vaish Diabetes & Metabolic Syndrome Clinical Research & Reviews	300
43	A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories Davide Placido, Bo Yuan, Jessica Xin Hjaltelin et al. Nature Medicine	300
44	A survey of GPT-3 family large language models including ChatGPT and GPT-4 Katikapalli Subramanyam Kalyan Natural Language Processing Journal	299
45	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	296
46	A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare Molla Imaduddin Ahmed, Brendan Spooner, John Isherwood et al. Cureus	291
47	A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges Qi An, Saifur Rahman, Jingwen Zhou et al. Sensors	290
48	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	287
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	285
50	Study and Analysis of Chat GPT and its Impact on Different Fields of Study Dinesh Kalla, Nathan Smith Zenodo (CERN European Organization for Nuclear Research)	284

Top Papers: Machine Learning im Gesundheitswesen (2023)

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