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TMU at TREC Clinical Trials Track 2023

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arxiv 2403.12088 v1 pith:Q5465PEG submitted 2024-03-12 cs.CL cs.IR

Aritra Kumar Lahiri , Emrul Hasan , Qinmin Vivian Hu , Cherie Ding This is my paper · ORCID
classification cs.CLcs.IR
keywords clinicaltrialslanguageparttracktrecadvanceddescribes
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper describes Toronto Metropolitan University's participation in the TREC Clinical Trials Track for 2023. As part of the tasks, we utilize advanced natural language processing techniques and neural language models in our experiments to retrieve the most relevant clinical trials. We illustrate the overall methodology, experimental settings, and results of our implementation for the run submission as part of Team - V-TorontoMU.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles

    cs.IR 2024-12 reject novelty 3.0 of 10

    AlzheimerRAG, a PubMed-based multimodal retrieval-augmented generation system, is reported, but its PubMedQA results are in-sample because PubMedQA was used for both fine-tuning and testing.

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