Publications (4)
Computational Drug Repositioning Using Continuous Self-controlled Case Series
Zhaobin Kuang, James Thomson, Michael Caldwell +3
Computational Drug Repositioning (CDR) is the task of discovering potential new indications for existing drugs by mining large-scale heterogeneous drug-related data sources. Levera…
CHAMMI-75: Pre-training multi-channel models with heterogeneous microscopy images
Vidit Agrawal, John Peters, Tyler N. Thompson +13
Quantifying cell morphology using images and machine learning has proven to be a powerful tool to study the response of cells to treatments. However, models used to quantify cellul…
Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered Tissues
Finn Kuusisto, Vitor Santos Costa, Zhonggang Hou +3
There is a growing need for fast and accurate methods for testing developmental neurotoxicity across several chemical exposure sources. Current approaches, such as in vivo animal s…
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
Finn Kuusisto, John Steill, Zhaobin Kuang +3
We present a simple text mining method that is easy to implement, requires minimal data collection and preparation, and is easy to use for proposing ranked associations between a l…