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Ehud Karavani
Researcher at Hebrew University of Jerusalem
Publications - 13
Citations - 266
Ehud Karavani is an academic researcher from Hebrew University of Jerusalem. The author has contributed to research in topics: Causal inference & Trait. The author has an hindex of 6, co-authored 9 publications receiving 136 citations. Previous affiliations of Ehud Karavani include IBM.
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Journal ArticleDOI
Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.
Ayelet Akselrod-Ballin,Michal Chorev,Yoel Shoshan,Adam Spiro,Alon Hazan,Roie Melamed,Ella Barkan,Esma Herzel,Shaked Naor,Ehud Karavani,Gideon Koren,Yaara Goldschmidt,Varda Shalev,Michal Rosen-Zvi,Michal Guindy +14 more
TL;DR: The algorithm, which combined machine-learning and deep-learning approaches, can be applied to assess breast cancer at a level comparable to radiologists and has the potential to substantially reduce missed diagnoses of breast cancer.
Journal ArticleDOI
Screening Human Embryos for Polygenic Traits Has Limited Utility.
Ehud Karavani,Or Zuk,Danny Zeevi,Nir Barzilai,Nikos C. Stefanis,Nikos C. Stefanis,Alex Hatzimanolis,Nikolaos Smyrnis,Nikolaos Smyrnis,Dimitrios Avramopoulos,Leonid Kruglyak,Gil Atzmon,Gil Atzmon,Max Lam,Max Lam,Todd Lencz,Todd Lencz,Shai Carmi +17 more
TL;DR: The potential gain of embryo screening is evaluated, defined as the difference in trait value between the top-scoring embryo and the average embryo, which increases very slowly with the number of embryos but more rapidly with the variance explained by the score.
Posted Content
Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis.
TL;DR: This work presents a comprehensive framework for benchmarking algorithms that estimate causal effect using data based on real-world covariates, and the treatment assignments and outcomes are based on simulations, which provides the basis for validation.
Journal ArticleDOI
In vivo cleavage rules and target repertoire of RNase III in Escherichia coli
TL;DR: This study provides a comprehensive map of the cleavage sites in both intra-molecular and inter-molescular duplex substrates, providing novel insights into the involvement of RNase III in post-transcriptional regulation in the bacterial cell.
Posted Content
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference.
Yishai Shimoni,Ehud Karavani,Sivan Ravid,Peter Bak,Tan Hung Ng,Sharon Hensley Alford,Denise Meade,Yaara Goldschmidt +7 more
TL;DR: This work developed a toolkit that expands established machine learning evaluation methods and adds several causal-specific ones, and is agnostic to the machine learning model that is used.