Top Papers: Radiologie (2025)

Die 50 meistzitierten Arbeiten zu Radiologie aus dem Jahr 2025 (von 1.473 insgesamt).

Die Radiologie gehört zu den Fachbereichen, in denen digitale Technologien besonders großen Einfluss haben. Automatisierte Befundungssysteme und KI-gestützte Bildanalysen ergänzen zunehmend die Arbeit von Radiologen. Gleichzeitig verändern sich Ausbildungskonzepte und Qualitätsstandards. Diese Übersicht zeigt die einflussreichsten Arbeiten und aktuellen Trends in der radiologischen Forschung.

2023 2024 2025 2026

#	Paper	Zitationen
1	Radiologic Technology Radiologic technology	278
2	Foundation Models in Radiology: What, How, Why, and Why Not Magdalini Paschali, Zhihong Chen, Louis Blankemeier et al. Radiology	60
3	Evaluating the performance of artificial intelligence-based speech recognition for clinical documentation: a systematic review Johan Y. Y. Ng, Eugene Wang, Xinyan Zhou et al. BMC Medical Informatics and Decision Making	44
4	Artificial Intelligence in Medical Education: Transforming Learning and Practice Aadhitya Sriram, Kalpana Ramachandran, Sriram Krishnamoorthy Cureus	42
5	Artificial Intelligence in Health Professions Education assessment: AMEE Guide No. 178 Ken Masters, Heather MacNeill, Jennifer Benjamin et al. Medical Teacher	37
6	The Growing Nationwide Radiologist Shortage: Current Opportunities and Ongoing Challenges for International Medical Graduate Radiologists Sohrab Afshari Mirak, Sree Harsha Tirumani, Nikhil H. Ramaiya et al. Radiology	34
7	Open-Source Large Language Models in Radiology: A Review and Tutorial for Practical Research and Clinical Deployment Cody Savage, Adway Kanhere, Vishwa S. Parekh et al. Radiology	33
8	Talk is cheap: why structural assessment changes are needed for a time of GenAI Thomas Corbin, Phillip Dawson, Danny Liu Assessment & Evaluation in Higher Education	33
9	CXR-LLaVA: a multimodal large language model for interpreting chest X-ray images Seowoo Lee, Jiwon Youn, Hyungjin Kim et al. European Radiology	31
10	Efficiency and Quality of Generative AI–Assisted Radiograph Reporting Jonathan Huang, Matthew T. Wittbrodt, Caitlin N. Teague et al. JAMA Network Open	29
11	Leveraging Large Language Models to Generate Clinical Histories for Oncologic Imaging Requisitions Rajesh Bhayana, Omar Alwahbi, Aly Muhammad Ladak et al. Radiology	29
12	Projected US Radiologist Supply, 2025 to 2055 Eric Christensen, Jay R. Parikh, Alexandra R. Drake et al. Journal of the American College of Radiology	29
13	Large language models for error detection in radiology reports: a comparative analysis between closed-source and privacy-compliant open-source models Babak Salam, Claire Stüwe, Sebastian Nowak et al. European Radiology	28
14	Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review R. C. Lawrence, Emma Dodsworth, Efthalia Massou et al. EClinicalMedicine	27
15	Unveiling GPT-4V's hidden challenges behind high accuracy on USMLE questions: Observational Study Zhichao Yang, Zonghai Yao, Mahbuba Tasmin et al. Journal of Medical Internet Research	26
16	Performance of DeepSeek-R1 and ChatGPT-4o on the Chinese National Medical Licensing Examination: A Comparative Study Jin Wu, Zhiheng Wang, Yifan Qin Journal of Medical Systems	26
17	Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study Danqing Hu, Shanyuan Zhang, Qing Liu et al. Journal of Medical Internet Research	26
18	Use of ChatGPT Large Language Models to Extract Details of Recommendations for Additional Imaging From Free-Text Impressions of Radiology Reports K Li, Ronilda Lacson, Jeffrey P. Guenette et al. American Journal of Roentgenology	24
19	Evaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis Nathaniel Barry, Jake Kendrick, Kaylee Molin et al. European Radiology	24
20	The need for balancing ’black box’ systems and explainable artificial intelligence: A necessary implementation in radiology Fabio De‐Giorgio, Beatrice Benedetti, Matteo Mancino et al. European Journal of Radiology	23
21	Situating governance and regulatory concerns for generative artificial intelligence and large language models in medical education Michael Tran, Chinthaka Balasooriya, Jitendra Jonnagaddala et al. npj Digital Medicine	22
22	Large-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports Songsoo Kim, Donghyun Kim, Hyun Joo Shin et al. Radiology	21
23	Integrating artificial intelligence into medical education: a roadmap informed by a survey of faculty and students Maria A. Blanco, Sara W. Nelson, Saradha Ramesh et al. Medical Education Online	21
24	Radiology-GPT: A large language model for radiology Zhengliang Liu, Yiwei Li, Peng Shu et al. Meta-Radiology	21
25	From technology adopters to creators: Leveraging AI-assisted vibe coding to transform clinical teaching and learning Minyang Chow, Olivia Ng Medical Teacher	20
26	Assessing the performance of Microsoft Copilot, GPT-4 and Google Gemini in ophthalmology Meziane Silhadi, Wissam B. Nassrallah, David Mikhail et al. Canadian Journal of Ophthalmology	18
27	The Integration of Cone Beam Computed Tomography, Artificial Intelligence, Augmented Reality, and Virtual Reality in Dental Diagnostics, Surgical Planning, and Education: A Narrative Review Aida Meto, Gerta Halilaj Applied Sciences	18
28	Guidelines and recommendations for radiologist staffing, education and training Adrian P. Brady, Christian Loewe, Boris Brkljačić et al. Insights into Imaging	18
29	A survey of deep-learning-based radiology report generation using multimodal inputs Xinyi Wang, Grazziela P. Figueredo, Ruizhe Li et al. Medical Image Analysis	18
30	Optimizing Large Language Models in Radiology and Mitigating Pitfalls: Prompt Engineering and Fine-tuning T. Kim, Michael Makutonin, Reza Sirous et al. Radiographics	18
31	Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students LI Rui-li, Guang‐Xue Liu, Miao Zhang et al. BMC Medical Education	18
32	Randomized Study of the Impact of AI on Perceived Legal Liability for Radiologists Michael H. Bernstein, Brian Sheppard, Michael A. Bruno et al. NEJM AI	18
33	AI Applications for Thoracic Imaging: Considerations for Best Practice Eui Jin Hwang, Jin Mo Goo, Chang Min Park Radiology	17
34	Automation bias in AI-assisted detection of cerebral aneurysms on time-of-flight MR angiography Su Hwan Kim, Severin Schramm, Evamaria Olga Riedel et al. La radiologia medica	17
35	The future of radiology: The path towards multimodal AI and superdiagnostics Felix Nensa European Journal of Radiology Artificial Intelligence	17
36	Evaluation of a Clinical Decision Support System for Imaging Requests Stijntje Dijk, Claudia Wollny, Jörg Barkhausen et al. JAMA	17
37	Recognising errors in AI implementation in radiology: A narrative review Nikolaos Stogiannos, Renato Cuocolo, Tugba Akinci D’Antonoli et al. European Journal of Radiology	17
38	Comparison between multimodal foundation models and radiologists for the diagnosis of challenging neuroradiology cases with text and images Bastien Le Guellec, Cyril Bruge, Najib Chalhoub et al. Diagnostic and Interventional Imaging	17
39	Evaluating ChatGPT’s diagnostic potential for pathology images Liya Ding, Lei Fan, Miao Shen et al. Frontiers in Medicine	16
40	Large Language Models in radiology: A technical and clinical perspective Jean Kao, Huan-Tang Kao European Journal of Radiology Artificial Intelligence	16
41	Artificial intelligence in radiology: 173 commercially available products and their scientific evidence Noa J.C. Antonissen, Olga Tryfonos, Ignas B. Houben et al. European Radiology	16
42	Evaluating the Efficacy of Perplexity Scores in Distinguishing AI-Generated and Human-Written Abstracts Alperen Elek, Hatice Sude Yildiz, Benan Akca et al. Academic Radiology	16
43	ChatGPT and oral cancer: a study on informational reliability Mesude Çıtır BMC Oral Health	16
44	Current applications and future perspectives of extended reality in radiology Mario Tortora, André Luppi, Francesco Pacchiano et al. La radiologia medica	16
45	Fine-tuning a local LLaMA-3 large language model for automated privacy-preserving physician letter generation in radiation oncology Yihao Hou, Christoph Bert, Ahmed M. Gomaa et al. Frontiers in Artificial Intelligence	15
46	Addressing cross-population domain shift in chest X-ray classification through supervised adversarial domain adaptation Ramli Musa, Rajesh Prasad, Monica Hernandez Scientific Reports	15
47	Provision of Radiology Reports Simplified With Large Language Models to Patients With Cancer: Impact on Patient Satisfaction Amit Gupta, Swarndeep Singh, Hema Malhotra et al. JCO Clinical Cancer Informatics	15
48	Intersections of Ergonomics and Radiation Safety in Interventional Radiology Halil SOYAL, Menşure Canpolat International Journal of Sustainable Science and Technology	15
49	Evaluating Artificial Intelligence in Patient Education: <scp>DeepSeek</scp> ‐ <scp>V3</scp> Versus <scp>ChatGPT</scp> ‐4o in Answering Common Questions on Laparoscopic Cholecystectomy Hilmi Anıl Dinçer, Doğukan Doğu ANZ Journal of Surgery	15
50	Best Practices for Large Language Models in Radiology Christian Blüthgen, Dave Van Veen, Cyril Zakka et al. Radiology	14

Top Papers: Radiologie (2025)

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