77 citations
- Harvard UniversityUS11 papers
- Brigham and Women's HospitalUS9 papers
- Harvard University PressUS7 papers
- Maastricht UniversityNL7 papers
- Dana-Farber Brigham Cancer CenterUS5 papers
- Charité - Universitätsmedizin BerlinDE4 papers
- Dana-Farber Cancer InstituteUS4 papers
- Humboldt-Universität zu BerlinDE4 papers
- Massachusetts Institute of TechnologyUS4 papers
- Technical University of MunichDE4 papers
- Boston Children's HospitalUS3 papers
- Cornell UniversityUS3 papers
5 papers · 1 filter
Preparing to Integrate Generative Pretrained Transformer Series 4 models into Genetic Variant Assessment Workflows: Assessing Performance, Drift, and Nondeterminism Characteristics Relative to Classifying Functional Evidence in Literature
Samuel J. Aronson, Kalotina Machini, Jiyeon Shin +8
Background. Large Language Models (LLMs) hold promise for improving genetic variant literature review in clinical testing. We assessed Generative Pretrained Transformer 4's (GPT-4)…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification
Shan Chen, Yingya Li, Sheng Lu +4
Recent advances in large language models (LLMs) have shown impressive ability in biomedical question-answering, but have not been adequately investigated for more specific biomedic…
Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy
Shan Chen, Marco Guevara, Nicolas Ramirez +7
Radiotherapy (RT) toxicities can impair survival and quality-of-life, yet remain under-studied. Real-world evidence holds potential to improve our understanding of toxicities, but…
MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain
Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann +12
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million Germ…