MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

2 code implementations • IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022 • Halil Ibrahim Kuru, Oznur Tastan, Ercument Cicek

Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side effects.

Focusing on Potential Named Entities During Active Label Acquisition

1 code implementation • 6 Nov 2021 • Ali Osman Berk Sapci, Oznur Tastan, Reyyan Yeniterzi

Named entity recognition (NER) aims to identify mentions of named entities in an unstructured text and classify them into predefined named entity classes.

Active Learning named-entity-recognition +3

Active Learning Methods based on Statistical Leverage Scores

no code implementations • 6 Dec 2018 • Cem Orhan, Oznur Tastan

Additionally, DBALEVS selects a diverse a set of examples that are highly representative but are dissimilar to already labeled examples through maximizing a submodular set function defined with the statistical leverage scores and the kernel matrix computed on the pool of the examples.

Active Learning