Search Results - "Gurulingappa, Harsha"

Extraction of potential adverse drug events from medical case reports by Gurulingappa, Harsha, Mateen-Rajput, Abdul, Toldo, Luca

“…: The sheer amount of information about potential adverse drug events published in medical case reports pose major challenges for drug safety experts to…”
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'HypothesisFinder:' a strategy for the detection of speculative statements in scientific text by Malhotra, Ashutosh, Younesi, Erfan, Gurulingappa, Harsha, Hofmann-Apitius, Martin

“…Speculative statements communicating experimental findings are frequently found in scientific articles, and their purpose is to provide an impetus for further…”
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Artificial intelligence-driven approach for patient-focused drug development by Karmalkar, Prathamesh, Gurulingappa, Harsha, Spies, Erica, Flynn, Jennifer A.

“…Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social…”
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Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson by Hatz, Sonja, Spangler, Scott, Bender, Andrew, Studham, Matthew, Haselmayer, Philipp, Lacoste, Alix M B, Willis, Van C, Martin, Richard L, Gurulingappa, Harsha, Betz, Ulrich

“…Pharmacodynamic biomarkers are becoming increasingly valuable for assessing drug activity and target modulation in clinical trials. However, identifying…”
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Weakly Supervised Learning for Categorization of Medical Inquiries for Customer Service Effectiveness by Singhal, Shikha, Hegde, Bharat, Karmalkar, Prathamesh, Muhith, Justna, Gurulingappa, Harsha

“…With the growing unstructured data in healthcare and pharmaceutical, there has been a drastic adoption of natural language processing for generating actionable…”
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Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports by Gurulingappa, Harsha, Rajput, Abdul Mateen, Roberts, Angus, Fluck, Juliane, Hofmann-Apitius, Martin, Toldo, Luca

“…[Display omitted] ► Benchmark corpus for adverse effect information extraction from free-text. ► Multiple annotations and thorough harmonization to ensure…”
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Artificial intelligence–enabled social media listening to inform early patient-focused drug development: perspectives on approaches and strategies by Spies, Erica, Flynn, Jennifer A., Oliveira, Nuno Guitian, Karmalkar, Prathamesh, Gurulingappa, Harsha

“…This article examines the opportunities and benefits of artificial intelligence (AI)–enabled social media listening (SML) in assisting successful…”
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Automatic detection of adverse events to predict drug label changes using text and data mining techniques by Gurulingappa, Harsha, Toldo, Luca, Rajput, Abdul Mateen, Kors, Jan A., Taweel, Adel, Tayrouz, Yorki

“…ABSTRACT Purpose The aim of this study was to assess the impact of automatically detected adverse event signals from text and open‐source data on the…”
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HypothesisFinder: A Strategy for the Detection of Speculative Statements in Scientific Text: e1003117 by Malhotra, Ashutosh, Younesi, Erfan, Gurulingappa, Harsha, Hofmann-Apitius, Martin

“…Speculative statements communicating experimental findings are frequently found in scientific articles, and their purpose is to provide an impetus for further…”
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Concept-Based Semi-Automatic Classification of Drugs by Gurulingappa, Harsha, Kolářik, Corinna, Hofmann-Apitius, Martin, Fluck, Juliane

“…The anatomical therapeutic chemical (ATC) classification system maintained by the World Health Organization provides a global standard for the classification…”
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"You are an expert annotator": Automatic Best-Worst-Scaling Annotations for Emotion Intensity Modeling by Bagdon, Christopher, Karmalker, Prathamesh, Gurulingappa, Harsha, Klinger, Roman

“…Labeling corpora constitutes a bottleneck to create models for new tasks or domains. Large language models mitigate the issue with automatic corpus labeling…”
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