activity
20222024
most citedUtilizing ChatGPT to Enhance Clinical Trial Enrollment

4 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2024

ASPIRE: Assistive System for Performance Evaluation in IR

Georgios Peikos, Wojciech Kusa, Symeon Symeonidis

Information Retrieval (IR) evaluation involves far more complexity than merely presenting performance measures in a table. Researchers often need to compare multiple models across…

cs.IR2024

Investigating Mixture of Experts in Dense Retrieval

Effrosyni Sokli, Pranav Kasela, Georgios Peikos +1

While Dense Retrieval Models (DRMs) have advanced Information Retrieval (IR), one limitation of these neural models is their narrow generalizability and robustness. To cope with th…

cs.IR20242 cited

Leveraging Large Language Models for Medical Information Extraction and Query Generation

Georgios Peikos, Pranav Kasela, Gabriella Pasi

This paper introduces a system that integrates large language models (LLMs) into the clinical trial retrieval process, enhancing the effectiveness of matching patients with eligibl…

cs.IR20234 cited

Utilizing ChatGPT to Enhance Clinical Trial Enrollment

Georgios Peikos, Symeon Symeonidis, Pranav Kasela +1

Clinical trials are a critical component of evaluating the effectiveness of new medical interventions and driving advancements in medical research. Therefore, timely enrollment of…

cs.IR2022

UNIMIB at TREC 2021 Clinical Trials Track

Georgios Peikos, Oscar Espitia, Gabriella Pasi

This contribution summarizes the participation of the UNIMIB team to the TREC 2021 Clinical Trials Track. We have investigated the effect of different query representations combine…