OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 25.03.2026, 14:40

Top Papers: KI in der Medizin (2021)

Die 50 meistzitierten Arbeiten zu KI in der Medizin aus dem Jahr 2021 (von 4.555 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.

#PaperZitationen
1

Artificial intelligence in healthcare: transforming the practice of medicine

Junaid Bajwa, Usman Munir, Aditya Nori et al.

Future Healthcare Journal

1.424
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

1.223
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

1.209
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

1.075
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

971
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

934
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

874
8

Privacy and artificial intelligence: challenges for protecting health information in a new era

Blake Murdoch

BMC Medical Ethics

849
9

Deep learning in histopathology: the path to the clinic

Jeroen van der Laak, Geert Litjens, Francesco Ciompi

Nature Medicine

829
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

814
11

Swarm Learning for decentralized and confidential clinical machine learning

Stefanie Warnat‐Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry et al.

Nature

798
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

770
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

739
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

702
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

691
16

AI applications to medical images: From machine learning to deep learning

Isabella Castiglioni, Leonardo Rundo, Marina Codari et al.

Physica Medica

672
17

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

671
18

Synthetic data in machine learning for medicine and healthcare

Richard J. Chen, Ming Y. Lu, Tiffany Chen et al.

Nature Biomedical Engineering

661
19

Federated learning for predicting clinical outcomes in patients with COVID-19

Ittai Dayan, Holger R. Roth, Aoxiao Zhong et al.

Nature Medicine

659
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

597
21

Transparency and the Black Box Problem: Why We Do Not Trust AI

Warren J. von Eschenbach

Philosophy & Technology

590
22

The Clinician and Dataset Shift in Artificial Intelligence

Samuel G. Finlayson, Adarsh Subbaswamy, Karandeep Singh et al.

New England Journal of Medicine

566
23

Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics

Jianlong Zhou, Amir H. Gandomi, Fang Chen et al.

Electronics

548
24

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

546
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

543
26

Digital pathology and artificial intelligence in translational medicine and clinical practice

Vipul Baxi, Robin Edwards, Michael Montalto et al.

Modern Pathology

526
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

513
28

Notions of explainability and evaluation approaches for explainable artificial intelligence

Giulia Vilone, Luca Longo

Information Fusion

505
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

489
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

458
31

Machine Learning in Healthcare

Hafsa Habehh, Suril Gohel

Current Genomics

449
32

AI for radiographic COVID-19 detection selects shortcuts over signal

Alex J. DeGrave, Joseph D. Janizek, Su‐In Lee

Nature Machine Intelligence

440
33

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

438
34

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

437
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

435
36

Ethical Machine Learning in Healthcare

Irene Y. Chen, Emma Pierson, Sherri Rose et al.

Annual Review of Biomedical Data Science

433
37

Formalizing Trust in Artificial Intelligence

Alon Jacovi, Ana Marasović, Tim Miller et al.

432
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

431
39

Encyclopedia of Artificial Intelligence

425
40

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

418
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)

415
42

Artificial intelligence in radiology: 100 commercially available products and their scientific evidence

Kicky G. van Leeuwen, Steven Schalekamp, Matthieu Rutten et al.

European Radiology

405
43

Second opinion needed: communicating uncertainty in medical machine learning

Benjamin Kompa, Jasper Snoek, Andrew L. Beam

npj Digital Medicine

397
44

Do as AI say: susceptibility in deployment of clinical decision-aids

Susanne Gaube, Harini Suresh, Martina Raue et al.

npj Digital Medicine

395
45

The Lancet Commission on diagnostics: transforming access to diagnostics

K A Fleming, Susan Horton, Michael L. Wilson et al.

The Lancet

395
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

386
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

386
48

Patient apprehensions about the use of artificial intelligence in healthcare

Jordan Richardson, Cambray Smith, Susan Curtis et al.

npj Digital Medicine

375
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

374
50

Health information technology and digital innovation for national learning health and care systems

Aziz Sheikh, Michael Anderson, Sarah Albala et al.

The Lancet Digital Health

349

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