Topic
Interpretability research, explained
4 open-access interpretability studies, each with a flashcard deck and a quiz.
- Can a transformer predict which cancer drug pairs work together?
Describing drugs by the proteins they affect and cells by which genes they depend on let a transformer predict drug-pair synergy better than an earlier chemistry-based network, while keeping predictions explainable gene by gene.
- Can machine learning build simple, readable hospital risk scores?
An automated method produced a nine-item point score for predicting hospital death that was almost as accurate as a black-box random forest while being simple enough to add up by hand.
- Can wiring a neural net by biology help small-data prognosis?
A neural network whose first connections follow known gene pathways, and which prunes itself to stay sparse, predicted brain-tumour survival slightly better than standard classifiers while being easier to interpret.
- When do a CNN's first filters learn whole DNA motifs?
CNNs only learn whole, readable DNA motifs in their first layer when the architecture stops deeper layers from assembling motifs out of pieces.