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Shreyasee Pradhan

Researcher at National University of Singapore

Publications -  8
Citations -  208

Shreyasee Pradhan is an academic researcher from National University of Singapore. The author has contributed to research in topics: Systematic review & Clinical trial. The author has an hindex of 7, co-authored 8 publications receiving 197 citations. Previous affiliations of Shreyasee Pradhan include Duke University.

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What Leads Indians to Participate in Clinical Trials? A Meta-Analysis of Qualitative Studies

TL;DR: Factors that facilitated and barriers that have negative implications on trial participation decisions in Indian subjects are identified and due consideration and weightage should be assigned to these factors while planning future trials in India.
Journal ArticleDOI

Electronic Data Capture for Registries and Clinical Trials in Orthopaedic Surgery: Open Source versus Commercial Systems

TL;DR: An overview of EDC systems, their types, and related pros and cons are provided as well as to describe commonly used EDC platforms and their features and simple steps involved in designing a registry/clinical study in DADOS P, an open source EDC system.
Proceedings ArticleDOI

Good to be Bad? Distinguishing between Positive and Negative Citations in Scientific Impact

TL;DR: In this article, the authors used sentiment analysis to rate citations as positive, neutral or negative, using the SentiWordNet lexicon to rate the degree of positivity and negativity for each adjective and then computed relevance scores to rank citations according to the sentiment expressed in the text corresponding to each citation.
Proceedings Article

Extracting Formulaic and Free Text Clinical Research Articles Metadata using Conditional Random Fields

TL;DR: This work explores the use of conditional random fields (CRFs) to automatically extract important metadata from clinical research articles to show an acceptable level of performance for formulaic metadata and a high precision for those found in the free text.
Journal ArticleDOI

Center of excellence in research reporting in neurosurgery--diagnostic ontology.

TL;DR: A computational diagnostic ontology is formulated containing 91 elements, including classes and sub-classes, which are required to conduct Systematic Reviews - Meta Analysis for diagnostic studies, which will assist in standardized reporting of diagnostic articles.