Top Papers: KI in der Medizin (2021)

Die 50 meistzitierten Arbeiten zu KI in der Medizin aus dem Jahr 2021 (von 4.561 insgesamt).

Die Forschung zu Künstlicher Intelligenz in der Medizin wächst rasant und verändert die Art, wie Krankheiten diagnostiziert und behandelt werden. Von der automatisierten Befundung über klinische Entscheidungsunterstützung bis hin zur personalisierten Therapie – KI-Systeme zeigen vielversprechende Ergebnisse in zahlreichen medizinischen Fachbereichen. Diese Seite fasst die aktuellsten und meistzitierten Forschungsarbeiten zusammen und zeigt, welche Institutionen und Forscher das Feld prägen.

2019 2020 2021 2022

#	Paper	Zitationen
1	Artificial intelligence in healthcare: transforming the practice of medicine Junaid Bajwa, Usman Munir, Aditya Nori et al. Future Healthcare Journal	1.457
2	Conceptualizing AI literacy: An exploratory review Davy Tsz Kit Ng, Jac Ka Lok Leung, Samuel Kai Wah Chu et al. Computers and Education Artificial Intelligence	1.264
3	The false hope of current approaches to explainable artificial intelligence in health care Marzyeh Ghassemi, Luke Oakden‐Rayner, Andrew L. Beam The Lancet Digital Health	1.231
4	A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19) Shuai Wang, Bo-Kyeong Kang, Jinlu Ma et al. European Radiology	1.076
5	The role of artificial intelligence in healthcare: a structured literature review Silvana Secinaro, Davide Calandra, Aurelio Secinaro et al. BMC Medical Informatics and Decision Making	984
6	Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges DonHee Lee, Seong No Yoon International Journal of Environmental Research and Public Health	941
7	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans Michael Roberts, Derek Driggs, Matthew Thorpe et al. Nature Machine Intelligence	886
8	Privacy and artificial intelligence: challenges for protecting health information in a new era Blake Murdoch BMC Medical Ethics	864
9	Deep learning in histopathology: the path to the clinic Jeroen van der Laak, Geert Litjens, Francesco Ciompi Nature Medicine	835
10	Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis Ravi Aggarwal, Viknesh Sounderajah, Guy Martin et al. npj Digital Medicine	826
11	Swarm Learning for decentralized and confidential clinical machine learning Stefanie Warnat‐Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry et al. Nature	808
12	Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction Laila Rasmy, Yang Xiang, Ziqian Xie et al. npj Digital Medicine	782
13	Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence Gary S. Collins, Paula Dhiman, Constanza L. Andaur Navarro et al. BMJ Open	754
14	Addressing bias in big data and AI for health care: A call for open science Natalia Norori, Qiyang Hu, Florence M. Aellen et al. Patterns	718
15	Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations Laleh Seyyed-Kalantari, Haoran Zhang, Matthew B. A. McDermott et al. Nature Medicine	703
16	Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond Guang Yang, Qinghao Ye, Jun Xia Information Fusion	677
17	AI applications to medical images: From machine learning to deep learning Isabella Castiglioni, Leonardo Rundo, Marina Codari et al. Physica Medica	677
18	Synthetic data in machine learning for medicine and healthcare Richard J. Chen, Ming Y. Lu, Tiffany Chen et al. Nature Biomedical Engineering	669
19	Federated learning for predicting clinical outcomes in patients with COVID-19 Ittai Dayan, Holger R. Roth, Aoxiao Zhong et al. Nature Medicine	669
20	Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis Urs J. Muehlematter, Paola Daniore, Kerstin Noëlle Vokinger The Lancet Digital Health	605
21	Transparency and the Black Box Problem: Why We Do Not Trust AI Warren J. von Eschenbach Philosophy & Technology	598
22	The Clinician and Dataset Shift in Artificial Intelligence Samuel G. Finlayson, Adarsh Subbaswamy, Karandeep Singh et al. New England Journal of Medicine	576
23	What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research Markus Langer, Daniel Oster, Timo Speith et al. Artificial Intelligence	558
24	Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics Jianlong Zhou, Amir H. Gandomi, Fang Chen et al. Electronics	551
25	Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review Anna Markella Antoniadi, Yuhan Du, Yasmine Guendouz et al. Applied Sciences	547
26	Digital pathology and artificial intelligence in translational medicine and clinical practice Vipul Baxi, Robin Edwards, Michael Montalto et al. Modern Pathology	533
27	Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology Jeremy Petch, Shuang Di, Walter Nelson Canadian Journal of Cardiology	521
28	Notions of explainability and evaluation approaches for explainable artificial intelligence Giulia Vilone, Luca Longo Information Fusion	516
29	Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review Lu Xu, Leslie Sanders, Kay Li et al. JMIR Cancer	497
30	Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions Valentin Kuleto, Milena Ilić, Mihail Alexandru Dumangiu et al. Sustainability	462
31	Machine Learning in Healthcare Hafsa Habehh, Suril Gohel Current Genomics	461
32	AI for radiographic COVID-19 detection selects shortcuts over signal Alex J. DeGrave, Joseph D. Janizek, Su‐In Lee Nature Machine Intelligence	449
33	Transparency of deep neural networks for medical image analysis: A review of interpretability methods Zohaib Salahuddin, Henry C. Woodruff, Avishek Chatterjee et al. Computers in Biology and Medicine	446
34	The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare Yuri Yin‐Moe Aung, David Wong, Daniel Shu Wei Ting British Medical Bulletin	445
35	End-to-end privacy preserving deep learning on multi-institutional medical imaging Georgios Kaissis, Alexander Ziller, Jonathan Passerat‐Palmbach et al. Nature Machine Intelligence	445
36	Ethical Machine Learning in Healthcare Irene Y. Chen, Emma Pierson, Sherri Rose et al. Annual Review of Biomedical Data Science	442
37	Formalizing Trust in Artificial Intelligence Alon Jacovi, Ana Marasović, Tim Miller et al. —	440
38	How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals Eric Q. Wu, Kevin Wu, Roxana Daneshjou et al. Nature Medicine	440
39	Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI Juan M. Durán, Karin Jongsma Journal of Medical Ethics	428
40	Encyclopedia of Artificial Intelligence —	425
41	A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle Harini Suresh, John V. Guttag DSpace@MIT (Massachusetts Institute of Technology)	422
42	The Lancet Commission on diagnostics: transforming access to diagnostics K A Fleming, Susan Horton, Michael L. Wilson et al. The Lancet	409
43	Artificial intelligence in radiology: 100 commercially available products and their scientific evidence Kicky G. van Leeuwen, Steven Schalekamp, Matthieu Rutten et al. European Radiology	409
44	Do as AI say: susceptibility in deployment of clinical decision-aids Susanne Gaube, Harini Suresh, Martina Raue et al. npj Digital Medicine	403
45	Second opinion needed: communicating uncertainty in medical machine learning Benjamin Kompa, Jasper Snoek, Andrew L. Beam npj Digital Medicine	403
46	Role of Artificial Intelligence Applications in Real-Life Clinical Practice: Systematic Review Jiamin Yin, Kee Yuan Ngiam, Hock‐Hai Teo Journal of Medical Internet Research	393
47	Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom Ellen Lee, John Torous, Munmun De Choudhury et al. Biological Psychiatry Cognitive Neuroscience and Neuroimaging	390
48	Patient apprehensions about the use of artificial intelligence in healthcare Jordan Richardson, Cambray Smith, Susan Curtis et al. npj Digital Medicine	380
49	Artificial intelligence for good health: a scoping review of the ethics literature Kathleen Murphy, Erica Di Ruggiero, Ross Upshur et al. BMC Medical Ethics	379
50	Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence Ekaterina Jussupow, Kai Spohrer, Armin Heinzl et al. Information Systems Research	356

Top Papers: KI in der Medizin (2021)

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