| MedAlpaca--an open-source collection of medical conversational AI models and training data T Han, LC Adams, JM Papaioannou, P Grundmann, T Oberhauser, ... arXiv preprint arXiv:2304.08247, 2023 | 270 | 2023 |
| The role of visceral adiposity in the severity of COVID-19: Highlights from a unicenter cross-sectional pilot study in Germany A Petersen, K Bressem, J Albrecht, HM Thieß, J Vahldiek, B Hamm, ... Metabolism 110, 154317, 2020 | 225 | 2020 |
| Comparing Different Deep Learning Architectures for Classification of Chest Radiographs KK Bressem, L Adams, C Erxleben, B Hamm, S Niehues, J Vahldiek Scientific Reports 10 (13590 (2020)), 2020 | 224 | 2020 |
| Leveraging GPT-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study LC Adams, D Truhn, F Busch, A Kader, SM Niehues, MR Makowski, ... Radiology 307 (4), e230725, 2023 | 210 | 2023 |
| Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases P Jurmeister, M Bockmayr, P Seegerer, T Bockmayr, D Treue, ... Science Translational Medicine 11 (509), eaaw8513, 2019 | 129 | 2019 |
| METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII B Kocak, T Akinci D’Antonoli, N Mercaldo, A Alberich-Bayarri, B Baessler, ... Insights into imaging 15 (1), 8, 2024 | 103 | 2024 |
| Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports KK Bressem, LC Adams, RA Gaudin, D Tröltzsch, B Hamm, MR Makowski, ... Bioinformatics 36 (21), 5255-5261, 2020 | 81 | 2020 |
| Renal cell carcinoma with venous extension: prediction of inferior vena cava wall invasion by MRI LC Adams, B Ralla, YNY Bender, K Bressem, B Hamm, J Busch, F Fuller, ... Cancer imaging 18, 1-9, 2018 | 81 | 2018 |
| What does DALL-E 2 know about radiology? LC Adams, F Busch, D Truhn, MR Makowski, HJWL Aerts, KK Bressem Journal of Medical Internet Research 25, e43110, 2023 | 64 | 2023 |
| Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance KK Bressem, JL Vahldiek, L Adams, SM Niehues, H Haibel, ... Arthritis Research & Therapy 23, 1-10, 2021 | 64 | 2021 |
| Prostate158-An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection LC Adams, MR Makowski, G Engel, M Rattunde, F Busch, P Asbach, ... Computers in Biology and Medicine 148, 105817, 2022 | 60 | 2022 |
| Biomedical ethical aspects towards the implementation of artificial intelligence in medical education F Busch, LC Adams, KK Bressem Medical science educator 33 (4), 1007-1012, 2023 | 51 | 2023 |
| Native T1 mapping as an in vivo biomarker for the identification of higher-grade renal cell carcinoma: correlation with histopathological findings LC Adams, B Ralla, P Jurmeister, KK Bressem, UL Fahlenkamp, B Hamm, ... Investigative radiology 54 (2), 118-128, 2019 | 44 | 2019 |
| Deep learning detects changes indicative of axial spondyloarthritis at MRI of sacroiliac joints KK Bressem, LC Adams, F Proft, KGA Hermann, T Diekhoff, L Spiller, ... Radiology 305 (3), 655-665, 2022 | 43 | 2022 |
| Use of quantitative T2 mapping for the assessment of renal cell carcinomas: first results LC Adams, KK Bressem, P Jurmeister, UL Fahlenkamp, B Ralla, G Engel, ... Cancer Imaging 19, 1-11, 2019 | 43 | 2019 |
| Non-alcoholic fatty liver disease in underweight patients with inflammatory bowel disease: A case-control study LC Adams, F Luebbe, K Bressem, M Wagner, B Hamm, MR Makowski PLoS One 13 (11), e0206450, 2018 | 39 | 2018 |
| Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions T Han, LC Adams, KK Bressem, F Busch, S Nebelung, D Truhn JAMA, 2024 | 37* | 2024 |
| A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reports D Truhn, CD Weber, BJ Braun, K Bressem, JN Kather, C Kuhl, ... Scientific Reports 13 (1), 20159, 2023 | 37 | 2023 |
| Extracting structured information from unstructured histopathology reports using generative pre‐trained transformer 4 (GPT‐4) D Truhn, CML Loeffler, G Müller‐Franzes, S Nebelung, KJ Hewitt, ... The Journal of Pathology 262 (3), 310-319, 2024 | 34 | 2024 |
| Multimodal deep learning for integrating chest radiographs and clinical parameters: a case for transformers F Khader, G Müller-Franzes, T Wang, T Han, S Tayebi Arasteh, ... Radiology 309 (1), e230806, 2023 | 34 | 2023 |