Towards Automated Detection of Contradictory Research Claims in Medical Literature Using Deep Learning Approach

FS Yazi, WT Vong, V Raman… - 2021 Fifth …, 2021 - ieeexplore.ieee.org
In Evidence-Based Medicine (EBM), medical literature is an essential resource used by
clinicians and researchers. It contains research claims that summarize the critical findings of …

Exploring Polypharmacy and Drug Interactions in Geriatric Patients: A Cross-Sectional Study from India

UF Khaiser, R Sultana, R Das, M Fareed, SS Abullais… - 2024 - researchsquare.com
Background Polypharmacy and potential drug-drug interactions (pDDIs) present challenges
in managing elderly individuals with multiple comorbidities. Understanding their prevalence …

A Study of Feature Extraction Methods and Corpora in Developing a Deep Neural Network Model for Contradictory Claims Detection in Medical Literature

FS Binti Yazi - 2022 - figshare.swinburne.edu.au
Clinicians or clinical researchers may encounter doubts or questions related to clinical tasks
or decision-making. To seek the answers to their questions, they will search and evaluate …

FINDING AND USING RESEARCH

KPGBL RAMJAN - Navigating the Maze of Research: Enhancing …, 2023 - books.google.com
Libraries collect, store and organise information and make it readily accessible for use.
Libraries can also direct users to other profession-specific repositories of information. Hard …

[PDF][PDF] Zheln. com: A protocol for a universal

P Zhelnov - PRISMA, 2020 - files.osf.io
BACKGROUND Objectives. 1. Identify and monitor most of published systematic reviews. 2.
Tag the identified systematic records with medical specialties. 3. Select or crowdfund …

Zheln. com: A protocol for a universal living overview of health-related systematic reviews

P Zhelnov - 2020 - osf.io
BACKGROUND Objectives. 1. Identify and monitor most of published systematic reviews. 2.
Tag the identified systematic records with medical specialties. 3. Select or crowdfund …

[引用][C] A Study of Feature Extraction Methods and Corpora in Developing a Deep Neural Network Model for Contradictory Claims Detection in Medical Literature