ML project, EPFL 2019 - Clustering tumor patients based on hormonal response
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Updated
Dec 19, 2019 - Jupyter Notebook
ML project, EPFL 2019 - Clustering tumor patients based on hormonal response
Codebase for the manuscript: "Personalized prescription of ACEI/ARBs for hypertensive COVID-19 patients"
Shrunk versus naive individual treatment effects in aggregated n-of-1 trials
R client to the Rx Studio APIs.
Precision Cancer Medicine.
cBioportal adaptor for creating PORI reports in IPR
A web application for stratification of Alzheimer's and Parkinson's disease patients
Methods for subgroup identification / personalized medicine / individualized treatment rules
Code to accompany the paper: "Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance"
Deep Treatment Learning (R)
A machine learning system for identification of ovarian response and deployment of ovarian stimulation strategies in ART
Benchmarking computational methods for B cell receptor reconstruction from single cell RNA-seq data
N-of-1 Companion is a web application designed to facilitate the conduct of N-of-1 therapeutic tests.
N-of-1 Companion is a web application designed to facilitate the conduct of N-of-1 therapeutic tests.
Shared package between the API and GUI for GraphKB which holds the schema definitions and schema-related functions
CrossTx: Cross-cell line Transcriptomic Signature Predictions
Determining the class of cancer-causing mutations using text and genetic data
Platform for Oncogenomic Reporting and Interpretation (PORI)
GPT-4-Powered Personalized Medical Bot
AI for early detection of neuroscience disorders
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