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Journal of Biomedical Semantics
|
December 22, 2012
Extraction of potential adverse drug events from medical case reports
Harsha Gurulingappa, Abdul Mateen-Rajput, Luca Toldo
Frontiers in Artificial Intelligence
|
October 30, 2023
Artificial intelligence-driven approach for patient-focused drug development
Prathamesh Karmalkar, Harsha Gurulingappa, Erica Spies, et al.
Journal of Chemical Information and Modeling
|
August 12, 2009
Concept-based semi-automatic classification of drugs
Harsha Gurulingappa, Corinna Kolárik, Martin Hofmann-Apitius, et al.
Plos Computational Biology
|
August 13, 2013
'HypothesisFinder:' a strategy for the detection of speculative statements in scientific text
Ashutosh Malhotra, Erfan Younesi, Harsha Gurulingappa, et al.
Frontiers in Research Metrics and Analytics
|
August 19, 2021
Weakly Supervised Learning for Categorization of Medical Inquiries for Customer Service Effectiveness
Shikha Singhal, Bharat Hegde, Prathamesh Karmalkar, et al.
Frontiers in Digital Health
|
December 5, 2024
Artificial intelligence-enabled social media listening to inform early patient-focused drug development: perspectives on approaches and strategies
Erica Spies, Jennifer A Flynn, Nuno Guitian Oliveira, et al.
Pharmacoepidemiology and Drug Safety
|
August 13, 2013
Automatic detection of adverse events to predict drug label changes using text and data mining techniques
Harsha Gurulingappa, Luca Toldo, Abdul Mateen Rajput, et al.
Journal of Biomedical Informatics
|
May 5, 2012
Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports
Harsha Gurulingappa, Abdul Mateen Rajput, Angus Roberts, et al.
Plos One
|
April 9, 2019
Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson
Sonja Hatz, Scott Spangler, Andrew Bender, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Journal of Biomedical Semantics
|
December 22, 2012
Extraction of potential adverse drug events from medical case reports
Harsha Gurulingappa, Abdul Mateen-Rajput, Luca Toldo
Frontiers in Artificial Intelligence
|
October 30, 2023
Artificial intelligence-driven approach for patient-focused drug development
Prathamesh Karmalkar, Harsha Gurulingappa, Erica Spies, et al.
Journal of Chemical Information and Modeling
|
August 12, 2009
Concept-based semi-automatic classification of drugs
Harsha Gurulingappa, Corinna Kolárik, Martin Hofmann-Apitius, et al.
Plos Computational Biology
|
August 13, 2013
'HypothesisFinder:' a strategy for the detection of speculative statements in scientific text
Ashutosh Malhotra, Erfan Younesi, Harsha Gurulingappa, et al.
Frontiers in Research Metrics and Analytics
|
August 19, 2021
Weakly Supervised Learning for Categorization of Medical Inquiries for Customer Service Effectiveness
Shikha Singhal, Bharat Hegde, Prathamesh Karmalkar, et al.
Frontiers in Digital Health
|
December 5, 2024
Artificial intelligence-enabled social media listening to inform early patient-focused drug development: perspectives on approaches and strategies
Erica Spies, Jennifer A Flynn, Nuno Guitian Oliveira, et al.
Pharmacoepidemiology and Drug Safety
|
August 13, 2013
Automatic detection of adverse events to predict drug label changes using text and data mining techniques
Harsha Gurulingappa, Luca Toldo, Abdul Mateen Rajput, et al.
Journal of Biomedical Informatics
|
May 5, 2012
Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports
Harsha Gurulingappa, Abdul Mateen Rajput, Angus Roberts, et al.
Plos One
|
April 9, 2019
Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson
Sonja Hatz, Scott Spangler, Andrew Bender, et al.
Page
of 1