Top Papers: KI in der Medizin (2020)

Die 50 meistzitierten Arbeiten zu KI in der Medizin aus dem Jahr 2020 (von 3.463 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.

2018 2019 2020 2021

#	Paper	Zitationen
1	The future of digital health with federated learning Nicola Rieke, Jonny Hancox, Wenqi Li et al. npj Digital Medicine	2.345
2	A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI Erico Tjoa, Cuntai Guan IEEE Transactions on Neural Networks and Learning Systems	2.072
3	Can AI Help in Screening Viral and COVID-19 Pneumonia? Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar et al. IEEE Access	1.881
4	Explainability for artificial intelligence in healthcare: a multidisciplinary perspective Julia Amann, Alessandro Blasimme, Effy Vayena et al. BMC Medical Informatics and Decision Making	1.720
5	The Ethics of AI Ethics: An Evaluation of Guidelines Thilo Hagendorff Minds and Machines	1.566
6	Artificial Intelligence (AI) applications for COVID-19 pandemic Raju Vaishya, Mohd Javaid, Ibrahim Haleem Khan et al. Diabetes & Metabolic Syndrome Clinical Research & Reviews	1.506
7	Artificial intelligence in drug discovery and development Debleena Paul, Gaurav Sanap, Snehal Shenoy et al. Drug Discovery Today	1.494
8	Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data Micah Sheller, Brandon Edwards, G. Anthony Reina et al. Scientific Reports	1.319
9	Secure, privacy-preserving and federated machine learning in medical imaging Georgios Kaissis, Marcus R. Makowski, Daniel Rückert et al. Nature Machine Intelligence	1.263
10	Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers John Mongan, Linda Moy, Charles E. Kahn Radiology Artificial Intelligence	1.186
11	Artificial Intelligence in Dentistry: Chances and Challenges Falk Schwendicke, Wojciech Samek, Joachim Krois Journal of Dental Research	1.152
12	The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI Donghee Shin International Journal of Human-Computer Studies	1.138
13	The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database Stan Benjamens, Pranavsingh Dhunnoo, Bertalan Meskó npj Digital Medicine	1.097
14	Artificial intelligence–enabled rapid diagnosis of patients with COVID-19 Xueyan Mei, Hao-Chih Lee, Kaiyue Diao et al. Nature Medicine	1.084
15	A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19) Shuai Wang, Bo-Kyeong Kang, Jinlu Ma et al. medRxiv	1.034
16	Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies Myura Nagendran, Yang Chen, Christopher A. Lovejoy et al. BMJ	1.021
17	Bias in data‐driven artificial intelligence systems—An introductory survey Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju et al. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery	961
18	Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine Zeeshan Ahmed, Khalid Gaffer Mohamed, Saman Zeeshan et al. Database	961
19	Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension Xiaoxuan Liu, Samantha Cruz Rivera, David Moher et al. Nature Medicine	948
20	Preparing Medical Imaging Data for Machine Learning Martin J. Willemink, Wojciech A. Koszek, Cailin Hardell et al. Radiology	942
21	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. Research Explorer (The University of Manchester)	937
22	Ethical and legal challenges of artificial intelligence-driven healthcare Sara Gerke, Timo Minssen, Glenn Cohen Elsevier eBooks	922
23	In AI we trust? Perceptions about automated decision-making by artificial intelligence Theo Araujo, Natali Helberger, Sanne Kruikemeier et al. AI & Society	910
24	Closing the AI accountability gap Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White et al. —	878
25	Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks Ali Abbasian Ardakani, Alireza Rajabzadeh Kanafi, U. Rajendra Acharya et al. Computers in Biology and Medicine	877
26	Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review Samuel Lalmuanawma, Jamal Hussain, Lalrinfela Chhakchhuak Chaos Solitons & Fractals	867
27	Artificial intelligence and the future of global health Nina Schwalbe, Brian Wahl The Lancet	852
28	The ethics of AI in health care: A mapping review Jessica Morley, Caio C. Vieira Machado, Christopher Burr et al. Social Science & Medicine	850
29	Automated machine learning: Review of the state-of-the-art and opportunities for healthcare Jonathan Waring, Charlotta Lindvall, Renato Umeton Artificial Intelligence in Medicine	827
30	Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians Onur Asan, Alparslan Emrah Bayrak, Avishek Choudhury Journal of Medical Internet Research	757
31	Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines Shih-Cheng Huang, Anuj Pareek, Saeed Seyyedi et al. npj Digital Medicine	756
32	COVID-CT-Dataset: A CT Scan Dataset about COVID-19 Yang, Xingyi, Xuehai He, Jinyu Zhao et al. arXiv (Cornell University)	728
33	The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek Journal of Biomedical Informatics	724
34	Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions J. Matthew Helm, Andrew Swiergosz, Heather S. Haeberle et al. Current Reviews in Musculoskeletal Medicine	674
35	Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis Ophir Gozes, Maayan Frid-Adar, Hayit Greenspan et al. arXiv (Cornell University)	672
36	Artificial Intelligence in Medicine: Today and Tomorrow Giovanni Briganti, Olivier Le Moine Frontiers in Medicine	654
37	AI in Medical Imaging Informatics: Current Challenges and Future Directions Andreas S. Panayides, Amir A. Amini, Nenad Filipović et al. IEEE Journal of Biomedical and Health Informatics	650
38	Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis Agostina J. Larrazabal, Nicolás Nieto, Victoria Peterson et al. Proceedings of the National Academy of Sciences	631
39	Bridging the Gap Between Ethics and Practice Ben Shneiderman ACM Transactions on Interactive Intelligent Systems	627
40	Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment Hema Sekhar Reddy Rajula, Giuseppe Verlato, Mirko Manchia et al. Medicina	581
41	The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment Melissa Haendel, Christopher G. Chute, Tellen D. Bennett et al. Journal of the American Medical Informatics Association	580
42	Artificial Intelligence, Values, and Alignment Iason Gabriel Minds and Machines	579
43	How Machine Learning Will Transform Biomedicine Jeremy Goecks, Vahid Jalili, Laura M. Heiser et al. Cell	577
44	Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension Samantha Cruz Rivera, Xiaoxuan Liu, An‐Wen Chan et al. Nature Medicine	562
45	Acknowledging the use of human cadaveric tissues in research papers: Recommendations from anatomical journal editors Joe Iwanaga, Vishram Singh, Aiji Ohtsuka et al. Clinical Anatomy	553
46	Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension Xiaoxuan Liu, Samantha Cruz Rivera, David Moher et al. BMJ	552
47	Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist Beau Norgeot, Giorgio Quer, Brett K. Beaulieu‐Jones et al. Nature Medicine	548
48	The Ethical Implications of Using Artificial Intelligence in Auditing Ivy Munoko, Helen L. Brown‐Liburd, Miklos A. Vasarhelyi Journal of Business Ethics	545
49	Generating Radiology Reports via Memory-driven Transformer Zhihong Chen, Yan Song, Tsung‐Hui Chang et al. —	541
50	The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review Madison Milne‐Ives, Caroline de Cock, Ernest Lim et al. Journal of Medical Internet Research	541

Top Papers: KI in der Medizin (2020)

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