588 citations · 807 across the 6 of their papers we have counts for
6 papers
Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale
Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee +6
Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data pr…
Scaling structural learning with NO-BEARS to infer causal transcriptome networks
Hao-Chih Lee, Matteo Danieletto, Riccardo Miotto +2
Constructing gene regulatory networks is a critical step in revealing disease mechanisms from transcriptomic data. In this work, we present NO-BEARS, a novel algorithm for estimati…
Enhancing high-content imaging for studying microtubule networks at large-scale
Hao-Chih Lee, Sarah T Cherng, Riccardo Miotto +1
Given the crucial role of microtubules for cell survival, many researchers have found success using microtubule-targeting agents in the search for effective cancer therapeutics. Un…
Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review
Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T Dudley +3
Of the 2652 articles considered, 106 met the inclusion criteria. Review of the included papers resulted in identification of 43 chronic diseases, which were then further classified…
Deep Learning Predicts Hip Fracture using Confounding Patient and Healthcare Variables
Marcus A. Badgeley, John R. Zech, Luke Oakden-Rayner +7
Hip fractures are a leading cause of death and disability among older adults. Hip fractures are also the most commonly missed diagnosis on pelvic radiographs. Computer-Aided Diagno…
Processing of Electronic Health Records using Deep Learning: A review
Venet Osmani, Li Li, Matteo Danieletto +3
Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of heal…