Ya'ara Goldschmidt
Ya'ara Goldschmidt
K Health
Verified email at khealth.ai - Homepage
Cited by
Cited by
Predicting breast cancer by applying deep learning to linked health records and mammograms
A Akselrod-Ballin, M Chorev, Y Shoshan, A Spiro, A Hazan, R Melamed, ...
Radiology 292 (2), 331-342, 2019
Changing the approach to treatment choice in epilepsy using big data
O Devinsky, C Dilley, M Ozery-Flato, R Aharonov, Y Goldschmidt, ...
Epilepsy & Behavior 56, 32-37, 2016
Paradoxical hypersusceptibility of drug-resistant mycobacteriumtuberculosis to β-lactam antibiotics
KA Cohen, T El-Hay, KL Wyres, O Weissbrod, V Munsamy, C Yanover, ...
EBioMedicine 9, 170-179, 2016
Modular memoization, tracking and train-data management of feature extraction
R Aharonov, Y Goldschmidt, M Ozery-Flato, C Yanover
US Patent 10,572,822, 2020
Estimating the effects of second-line therapy for type 2 diabetes mellitus: retrospective cohort study
A Gottlieb, C Yanover, A Cahan, Y Goldschmidt
BMJ Open Diabetes Research and Care 5 (1), 2017
Integrated multisystem analysis in a mental health and criminal justice ecosystem
E Falconer, T El-Hay, D Alevras, JP Docherty, C Yanover, A Kalton, ...
Health & justice 5 (1), 1-8, 2017
Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
Z Waks, O Weissbrod, B Carmeli, R Norel, F Utro, Y Goldschmidt
Scientific reports 6 (1), 1-12, 2016
Smarter log analysis
E Aharoni, S Fine, Y Goldschmidt, O Lavi, O Margalit, M Rosen-Zvi, ...
IBM Journal of Research and Development 55 (5), 10: 1-10: 10, 2011
Fast multilevel clustering
Y Goldschmidt, M Galun, E Sharon, R Basri, A Brandt
Adaptive methods for classification of biological microarray data from multiple experiments
Y Goldschmidt, E Sharon, FJ Quintana, IR Cohen, A Brandt
Fast and efficient feature engineering for multi-cohort analysis of EHR data
M Ozery-Flato, C Yanover, A Gottlieb, O Weissbrod, ...
Stud Health Technol Inform 235, 181-5, 2017
Automatic detection of anomalies in graphs
Y Goldschmidt, O Lavi, M Ninio
US Patent 9,245,233, 2016
Automatic detection of anomalies in graphs
Y Goldschmidt, O Lavi, M Ninio
US Patent 9,245,233, 2016
Workflow validation and execution
E Aharoni, Y Goldschmidt, T Lavee, H Neuvirth-Telem
US Patent 8,601,481, 2013
An evaluation toolkit to guide model selection and cohort definition in causal inference
Y Shimoni, E Karavani, S Ravid, P Bak, TH Ng, SH Alford, D Meade, ...
arXiv preprint arXiv:1906.00442, 2019
A standard based approach for biomedical knowledge representation
A Farkash, H Neuvirth, Y Goldschmidt, C Conti, F Rizzi, S Bianchi, E Salvi, ...
Conference of the European Federation of Medical Informatics (MIE): August …, 2011
Automatic detection of anomalies in graphs
Y Goldschmidt, O Lavi, M Ninio
US Patent App. 14/839,981, 2016
Framework for identifying drug repurposing candidates from observational healthcare data
M Ozery-Flato, Y Goldschmidt, O Shaham, S Ravid, C Yanover
medRxiv, 2020
Characterizing Subpopulations with Better Response to Treatment Using Observational Data-an Epilepsy Case Study
M Ozery-Flato, T El-Hay, R Aharonov, N Parush-Shear-Yashuv, ...
bioRxiv, 290585, 2018
Characteristics and Symptoms of App Users Seeking COVID-19–Related Digital Health Information and Remote Services: Retrospective Cohort Study
A Perlman, AV Zilberg, P Bak, M Dreyfuss, M Leventer-Roberts, ...
Journal of medical Internet research 22 (10), e23197, 2020
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