Published October 19, 2024 | Version v1
Conference paper

ANTIDOTE: ArgumeNtaTIon-Driven explainable artificial intelligence fOr digiTal mEdicine

Description

The need for transparent AI systems in sensitive domains like medicine has become key. In this paper we present ANTIDOTE, a software suite proposing different tools for argumentation-driven explainable Artificial Intelligence for digital medicine. Our system offers the following functionalities: multilingual argumentative analysis for the medical domain, explanation extraction and generation of clinical diagnoses, multilingual large language models for the medical domain, and the first multilingual benchmark for medical question-answering. Experimental results demonstrate the efficacy of ANTIDOTE across different tasks, highlighting its potential as an asset in medical research and practice and fostering transparency, which is crucial for informed decision-making in healthcare.

Abstract

International audience

Additional details

Identifiers

URL
https://hal.science/hal-04673974
URN
urn:oai:HAL:hal-04673974v1

Origin repository

Origin repository
UNICA