Work

KATY — Knowledge At the Tip of Your fingers: Clinical Knowledge for Humanity

Year: 2025

Type: conference-paper

Abstract: The KATY project aims to develop an AI-empowered personalised medicine system to assist medical professionals and researchers in diagnosing patients more accurately, making predictions about their future health, and recommending better treatments. KATY will tackle the challenge of translating AI-based suggestions into practical decision-making processes and treatment strategies that clinicians can understand and trust by combining high-performing black-box machine learning approaches with a comprehensive knowledge graph. The knowledge graph serves as input to AI methods (e.g. directly, through embeddings) as well as encodes the AI outcomes themselves to create a shared semantic space for data, scientifi c context and predictions capable of supporting explanation methods.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15609793

Authors: Silva, Marta C., Nunes, Susana, Balbi, Laura, Rodrigues, Ana Filipa, Pesquita, Catia

Institution: University of Lisbon

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funder: European Commission