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Related Experiment Video

Updated: Jul 7, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Question processing and clustering in INDOC: a biomedical question answering system.

Parikshit Sondhi¹, Purushottam Raj, V Vinod Kumar

¹Department of Electronics and Computer Engineering, Indian Institute of Technology-Roorkee, Roorkee, India.

EURASIP Journal on Bioinformatics & Systems Biology

|February 16, 2008

Summary

Biomedical question answering systems are crucial for physicians. INDOC, a novel system, quickly retrieves accurate answers from publications, minimizing user effort and improving information access.

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Last Updated: Jul 7, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

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Published on: February 23, 2019

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

Biomedical Informatics
Information Retrieval
Medical Artificial Intelligence

Background:

The rapid increase in biomedical publications challenges information access for healthcare professionals.
Physicians face difficulties in retrieving timely, relevant evidence for clinical decision-making.
Existing systems often lack the speed and accuracy needed for real-time medical queries.

Purpose of the Study:

To introduce INDOC, a novel biomedical question answering system.
To address the need for fast and accurate information retrieval in the biomedical domain.
To enhance physicians' ability to access critical information efficiently.

Main Methods:

Developed INDOC utilizing innovative indexing and answer extraction techniques.
Implemented a clustering approach to present search results, facilitating rapid document identification.
Evaluated system performance using the standard OHSUMED test collection.

Main Results:

INDOC demonstrated high accuracy in answering biomedical questions.
The system significantly reduced the time and effort required for users to find relevant documents.
Clustered results effectively guided users to the most pertinent information.

Conclusions:

INDOC offers a promising solution for overcoming information overload in medicine.
The system enhances the accessibility of evidence-based medicine for clinical practice.
INDOC's approach to indexing and retrieval improves efficiency for biomedical information seeking.