1 code implementation • 29 Feb 2024 • Keying Kuang, Frances Dean, Jack B. Jedlicki, David Ouyang, Anthony Philippakis, David Sontag, Ahmed M. Alaa
A digital twin is a virtual replica of a real-world physical phenomena that uses mathematical modeling to characterize and simulate its defining features.
no code implementations • 23 Feb 2024 • Ilker Demirel, Edward De Brouwer, Zeshan Hussain, Michael Oberst, Anthony Philippakis, David Sontag
Drawing causal inferences from observational studies (OS) requires unverifiable validity assumptions; however, one can falsify those assumptions by benchmarking the OS with experimental data from a randomized controlled trial (RCT).
no code implementations • 1 Dec 2023 • Bum Chul Kwon, Samuel Friedman, Kai Xu, Steven A Lubitz, Anthony Philippakis, Puneet Batra, Patrick T Ellinor, Kenney Ng
Machine learning models built on training data with multiple modalities can reveal new insights that are not accessible through unimodal datasets.
no code implementations • 16 Nov 2023 • Ayush Jain, Marie Laure-Charpignon, Irene Y. Chen, Anthony Philippakis, Ahmed Alaa
Cosine similarity values are computed between (1) all biological pathways starting at the considered drug and ending at the disease of interest and (2) all biological pathways starting at drugs currently prescribed against that disease and ending at the disease of interest.
1 code implementation • 30 Sep 2023 • Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed M. Alaa
We then use a large language model to paraphrase prompt templates that convey the specific tasks to be conducted on each image, and through this process, we create a multi-modal and multi-task training dataset comprising input and output images along with annotated instructions.
1 code implementation • 20 Sep 2023 • Jose Roberto Tello Ayala, Akl C. Fahed, Weiwei Pan, Eugene V. Pomerantsev, Patrick T. Ellinor, Anthony Philippakis, Finale Doshi-Velez
The adoption of machine learning in healthcare calls for model transparency and explainability.