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Kira Radinsky

Showing results (1-10 of 17) with videos related to

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Molecular Pharmaceutics|August 1, 2018
Prototype-Based Compound Discovery Using Deep Generative ModelsShahar Harel, Kira Radinsky
JMIR AI|October 2, 2024
Leveraging Temporal Trends for Training Contextual Word Embeddings to Address Bias in Biomedical Applications: Development StudyShunit Agmon, Uriel Singer, Kira Radinsky
Bioinformatics (Oxford, England)|December 16, 2020
On biases of attention in scientific discoveryUriel Singer, Kira Radinsky, Eric Horvitz
Bioinformatics (Oxford, England)|August 12, 2025
Beyond the leaderboard: leveraging predictive modeling for protein-ligand insights and discoveryDan Kalifa, Kira Radinsky, Eric Horvitz
Bioinformatics (Oxford, England)|May 5, 2026
Learning Protein Representations with Conformational DynamicsDan Kalifa, Eric Horvitz, Kira Radinsky
Expert Review of Clinical Pharmacology|June 25, 2019
Clinical pharmacology of old ageGideon Koren, Galia Nordon, Kira Radinsky, et al.
Journal of Chemical Information and Modeling|May 28, 2025
Predicting Oxidation Potentials with DFT-Driven Machine LearningShweta Sharma, Natan Kaminsky, Kira Radinsky, et al.
Clinical Drug Investigation|March 15, 2019
Chronic Use of β-Blockers and the Risk of Parkinson's DiseaseGideon Koren, Galia Norton, Kira Radinsky, et al.
Pharmacology Research & Perspectives|November 26, 2019
Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learningGideon Koren, Galia Nordon, Kira Radinsky, et al.
Pharmacology Research & Perspectives|May 4, 2018
Machine learning of big data in gaining insight into successful treatment of hypertensionGideon Koren, Galia Nordon, Kira Radinsky, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Molecular Pharmaceutics|August 1, 2018
Prototype-Based Compound Discovery Using Deep Generative ModelsShahar Harel, Kira Radinsky
JMIR AI|October 2, 2024
Leveraging Temporal Trends for Training Contextual Word Embeddings to Address Bias in Biomedical Applications: Development StudyShunit Agmon, Uriel Singer, Kira Radinsky
Bioinformatics (Oxford, England)|December 16, 2020
On biases of attention in scientific discoveryUriel Singer, Kira Radinsky, Eric Horvitz
Bioinformatics (Oxford, England)|August 12, 2025
Beyond the leaderboard: leveraging predictive modeling for protein-ligand insights and discoveryDan Kalifa, Kira Radinsky, Eric Horvitz
Bioinformatics (Oxford, England)|May 5, 2026
Learning Protein Representations with Conformational DynamicsDan Kalifa, Eric Horvitz, Kira Radinsky
Expert Review of Clinical Pharmacology|June 25, 2019
Clinical pharmacology of old ageGideon Koren, Galia Nordon, Kira Radinsky, et al.
Journal of Chemical Information and Modeling|May 28, 2025
Predicting Oxidation Potentials with DFT-Driven Machine LearningShweta Sharma, Natan Kaminsky, Kira Radinsky, et al.
Clinical Drug Investigation|March 15, 2019
Chronic Use of β-Blockers and the Risk of Parkinson's DiseaseGideon Koren, Galia Norton, Kira Radinsky, et al.
Pharmacology Research & Perspectives|November 26, 2019
Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learningGideon Koren, Galia Nordon, Kira Radinsky, et al.
Pharmacology Research & Perspectives|May 4, 2018
Machine learning of big data in gaining insight into successful treatment of hypertensionGideon Koren, Galia Nordon, Kira Radinsky, et al.
Pageof 2