1 code implementation • 9 May 2024 • Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo Aerts, Brian Anthony, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data.
1 code implementation • 28 Mar 2024 • Shan Chen, Jack Gallifant, Marco Guevara, Yanjun Gao, Majid Afshar, Timothy Miller, Dmitriy Dligach, Danielle S. Bitterman
Generative models have been showing potential for producing data in mass.
1 code implementation • 26 Oct 2023 • Shan Chen, Marco Guevara, Shalini Moningi, Frank Hoebers, Hesham Elhalawani, Benjamin H. Kann, Fallon E. Chipidza, Jonathan Leeman, Hugo J. W. L. Aerts, Timothy Miller, Guergana K. Savova, Raymond H. Mak, Maryam Lustberg, Majid Afshar, Danielle S. Bitterman
Results show promise for AI to improve clinician efficiency and patient care through assisting documentation, if used judiciously.
1 code implementation • 11 Aug 2023 • Marco Guevara, Shan Chen, Spencer Thomas, Tafadzwa L. Chaunzwa, Idalid Franco, Benjamin Kann, Shalini Moningi, Jack Qian, Madeleine Goldstein, Susan Harper, Hugo JWL Aerts, Guergana K. Savova, Raymond H. Mak, Danielle S. Bitterman
The study also experimented with synthetic data generation and assessed for algorithmic bias.
1 code implementation • 5 Apr 2023 • Shan Chen, Yingya Li, Sheng Lu, Hoang Van, Hugo JWL Aerts, Guergana K. Savova, Danielle S. Bitterman
The first task is classifying whether statements of clinical and policy recommendations in scientific literature constitute health advice.
1 code implementation • 24 Mar 2023 • Shan Chen, Marco Guevara, Nicolas Ramirez, Arpi Murray, Jeremy L. Warner, Hugo JWL Aerts, Timothy A. Miller, Guergana K. Savova, Raymond H. Mak, Danielle S. Bitterman
We developed natural language processing (NLP) models to identify the presence and severity of esophagitis from notes of patients treated with thoracic RT.