Top Papers: Machine Learning im Gesundheitswesen (2022)

Die 50 meistzitierten Arbeiten zu Machine Learning im Gesundheitswesen aus dem Jahr 2022 (von 5.315 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.

2020 2021 2022 2023

#	Paper	Zitationen
1	Multimodal biomedical AI Julián Acosta, Guido J. Falcone, Pranav Rajpurkar et al. Nature Medicine	1.056
2	Towards Personalized Federated Learning Alysa Ziying Tan, Han Yu, Lizhen Cui et al. IEEE Transactions on Neural Networks and Learning Systems	987
3	On evaluation metrics for medical applications of artificial intelligence Steven A. Hicks, Inga Strümke, Vajira Thambawita et al. Scientific Reports	816
4	A large language model for electronic health records Xi Yang, Aokun Chen, Nima PourNejatian et al. npj Digital Medicine	804
5	Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022) Hui Wen Loh, Chui Ping Ooi, Silvia Seoni et al. Computer Methods and Programs in Biomedicine	666
6	Frontiers in Artificial Intelligence and Applications Jaya Yadav, Shruti Shukla, Kanika Sharma et al. —	661
7	Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models Tiffany H. Kung, Morgan Cheatham, ChatGPT et al. medRxiv	617
8	Communication-efficient federated learning via knowledge distillation Chuhan Wu, Fangzhao Wu, Lingjuan Lyu et al. Nature Communications	544
9	Federated Learning for Healthcare: Systematic Review and Architecture Proposal Rodolfo Stoffel Antunes, Cristiano André da Costa, Arne Küderle et al. ACM Transactions on Intelligent Systems and Technology	526
10	Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan, Haiyang Yu, Shurui Gui et al. IEEE Transactions on Pattern Analysis and Machine Intelligence	493
11	What Makes Good In-Context Examples for GPT-3? Jiachang Liu, Dinghan Shen, Yizhe Zhang et al. —	490
12	Interpreting area under the receiver operating characteristic curve Anne de Hond, Ewout W. Steyerberg, Ben Van Calster The Lancet Digital Health	466
13	Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI Baptiste Vasey, Myura Nagendran, Bruce Campbell et al. Nature Medicine	465
14	Explainable AI for Healthcare 5.0: Opportunities and Challenges Deepti Saraswat, Pronaya Bhattacharya, Ashwin Verma et al. IEEE Access	446
15	Multimodal machine learning in precision health: A scoping review Adrienne Kline, Hanyin Wang, Yikuan Li et al. npj Digital Medicine	437
16	MONAI: An open-source framework for deep learning in healthcare M. Jorge Cardoso, Wenqi Li, Richard Brown et al. arXiv (Cornell University)	431
17	Natural language processing applied to mental illness detection: a narrative review Tianlin Zhang, Annika Marie Schoene, Shaoxiong Ji et al. npj Digital Medicine	417
18	Shifting machine learning for healthcare from development to deployment and from models to data Angela Zhang, Lei Xing, James Zou et al. Nature Biomedical Engineering	388
19	Counterfactual explanations and how to find them: literature review and benchmarking Riccardo Guidotti Data Mining and Knowledge Discovery	386
20	Explainable AI Methods - A Brief Overview Andreas Holzinger, Anna Saranti, Christoph Molnar et al. Lecture notes in computer science	356
21	GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Qiang Huang, Makoto Yamada, Yuan Tian et al. IEEE Transactions on Knowledge and Data Engineering	353
22	Multimodal deep learning for Alzheimer’s disease dementia assessment Shangran Qiu, Matthew I. Miller, Prajakta Joshi et al. Nature Communications	347
23	Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare Jean Feng, Rachael V. Phillips, Ivana Malenica et al. npj Digital Medicine	340
24	Explainable, trustworthy, and ethical machine learning for healthcare: A survey Khansa Rasheed, Adnan Qayyum, Mohammed Ghaly et al. Computers in Biology and Medicine	320
25	A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods Timo Speith 2022 ACM Conference on Fairness, Accountability, and Transparency	309
26	Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis Roy J. Adams, Katharine E. Henry, Anirudh Sridharan et al. Nature Medicine	297
27	Integrated multimodal artificial intelligence framework for healthcare applications Luis R. Soenksen, Yu Ma, Cynthia Zeng et al. npj Digital Medicine	297
28	DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lü, Yuhao Zhou, Fan Bao et al. arXiv (Cornell University)	289
29	Prediction of Diabetes Empowered With Fused Machine Learning Usama Ahmed, Ghassan F. Issa, Muhammad Adnan Khan et al. IEEE Access	284
30	Diffusion Models for Medical Anomaly Detection Julia Wolleb, Florentin Bieder, Robin Sandkühler et al. Lecture notes in computer science	283
31	ChatGPT: Fundamentals, Applications and Social Impacts Malak Abdullah, Alia Madain, Yaser Jararweh —	282
32	Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review Sheela Kolluri, Jianchang Lin, Rachael Liu et al. The AAPS Journal	269
33	Artificial intelligence in nursing and midwifery: A systematic review Siobhán O’Connor, Yongyang Yan, Friederike J.S. Thilo et al. Journal of Clinical Nursing	268
34	Efficient Medical Diagnosis of Human Heart Diseases Using Machine Learning Techniques With and Without GridSearchCV Ghulab Nabi Ahmad, Hira Fatima, Shafi Ullah et al. IEEE Access	258
35	IoT-Cloud-Based Smart Healthcare Monitoring System for Heart Disease Prediction via Deep Learning A Angel Nancy, D. Ravindran, P. M. Durai Raj Vincent et al. Electronics	252
36	Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey Mingyang Chen, Bo Zhang, Ziting Cai et al. Frontiers in Medicine	245
37	Ethical, legal, and social considerations of AI-based medical decision-support tools: A scoping review Anto Čartolovni, Ana Tomičić, Elvira Lazić Mosler International Journal of Medical Informatics	244
38	A Deep Neural Network for Early Detection and Prediction of Chronic Kidney Disease Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran Diagnostics	240
39	Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review Haomin Chen, Catalina Gómez, Chien‐Ming Huang et al. npj Digital Medicine	237
40	Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective Chollette C. Olisah, Lyndon Smith, Melvyn Smith Computer Methods and Programs in Biomedicine	235
41	A Novel Diabetes Healthcare Disease Prediction Framework Using Machine Learning Techniques R. Krishnamoorthi, Shubham Joshi, Hatim Z. Almarzouki et al. Journal of Healthcare Engineering	233
42	Explaining a series of models by propagating Shapley values Hugh Chen, Scott Lundberg, Su‐In Lee Nature Communications	232
43	Neural Natural Language Processing for unstructured data in electronic health records: A review Irene Li, Jessica Pan, Jeremy Goldwasser et al. Computer Science Review	229
44	Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research AKM Bahalul Haque, A.K.M. Najmul Islam, Patrick Mikalef Technological Forecasting and Social Change	219
45	Explainable Artificial Intelligence for Predictive Modeling in Healthcare Christopher C. Yang Journal of Healthcare Informatics Research	215
46	A systematic review of the prediction of hospital length of stay: Towards a unified framework Kieran Stone, Reyer Zwiggelaar, P. D. Jones et al. PLOS Digital Health	210
47	VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients Hyung‐Chul Lee, Yoonsang Park, Soo Bin Yoon et al. Scientific Data	209
48	Randomized Clinical Trials of Machine Learning Interventions in Health Care Deborah Plana, Dennis Shung, Alyssa Grimshaw et al. JAMA Network Open	206
49	Artificial intelligence-based methods for fusion of electronic health records and imaging data Farida Mohsen, Hazrat Ali, Nady El Hajj et al. Scientific Reports	206
50	Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges Alan J. Meehan, Stephanie J. Lewis, Seena Fazel et al. Molecular Psychiatry	202

Top Papers: Machine Learning im Gesundheitswesen (2022)

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