The Lancet

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study

aTaub Faculty of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel bFaculty of Electrical and Computer Engineering, Technion-Israel Institute of Technology, Haifa, Israel ...
ahajournals.org

Functional Outcome Prediction in Acute Ischemic Stroke Using a Fused Imaging and Clinical Deep Learning Model

Predicting long-term clinical outcome based on the early acute ischemic stroke information is valuable for prognostication, resource management, clinical trials, and patient expectations. Current ...
Frontiers

MapCell: Learning a Comparative Cell Type Distance Metric With Siamese Neural Nets With Applications Toward Cell-Type Identification Across Experimental Datasets

Large collections of annotated single-cell RNA sequencing (scRNA-seq) experiments are being generated across different organs, conditions and organisms on different platforms. The diversity, volume ...
eLife

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored ...
PNAS

Programming and training rate-independent chemical reaction networks

To program complex behavior in environments incompatible with electronic controllers such as within bioreactors or engineered cells, we turn to chemical information processors. While chemical ...
Frontiers

Connectome-Based Model Predicts Deep Brain Stimulation Outcome in Parkinson's Disease

Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective invasive treatment for advanced Parkinson's disease (PD) at present. Due to the invasiveness and cost of operations, a reliable ...