Explainable AI-Based Semantic Retrieval from an Expert-Curated Oncology Knowledge Graph for Clinical Decision Support

The modern oncology landscape is characterised by a deluge of high-dimensional data from genomic sequencing, medical imaging, and electronic health records, negatively impacting the analytical capacity of clinicians and health practitioners. This field is not new and it has drawn significant attention from the research community. However, one of the main limiting issues is the data itself. Despite the vast amount of available data, most of it lacks scalability, quality, and semantic information. This work is motivated by the data platform provided by OncoProAI, an AI-driven clinical decision support platform designed to address this challenge by enabling highly personalised, precision cancer care. The platform is built on a comprehensive knowledge graph, formally modelled as a directed acyclic graph, which has been manually populated, assessed and maintained to provide a unique data ecosystem. This enables targeted and bespoke information extraction and assessment.

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Publication Details

Journal
Future Internet
Published
2025-10-16
DOI
https://doi.org/10.3390/fi17100471
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Explainable AI-Based Semantic Retrieval from an Expert-Curated Oncology Knowledge Graph for Clinical Decision Support

Nik Bessis, Marcello Trovati, Sameer Mushtaq
Future Internet
Radiomics and Machine Learning in Medical Imaging
article

Explainable AI-Based Semantic Retrieval from an Expert-Curated Oncology Knowledge Graph for Clinical Decision Support

Nik Bessis, Marcello Trovati, Sameer Mushtaq
article en

Abstract

The modern oncology landscape is characterised by a deluge of high-dimensional data from genomic sequencing, medical imaging, and electronic health records, negatively impacting the analytical capacity of clinicians and health practitioners. This field is not new and it has drawn significant attention from the research community. However, one of the main limiting issues is the data itself. Despite the vast amount of available data, most of it lacks scalability, quality, and semantic information. This work is motivated by the data platform provided by OncoProAI, an AI-driven clinical decision support platform designed to address this challenge by enabling highly personalised, precision cancer care. The platform is built on a comprehensive knowledge graph, formally modelled as a directed acyclic graph, which has been manually populated, assessed and maintained to provide a unique data ecosystem. This enables targeted and bespoke information extraction and assessment.

Future InternetVol. 17(10)
Edge Hill University (GB), University of Lancashire (GB)
Openalex Percentile: Top 56%
Radiomics and Machine Learning in Medical Imaging
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Explainable AI-Based Semantic Retrieval from an Expert-Curated Oncology Knowledge Graph for Clinical Decision Support — Nik Bessis, Marcello Trovati, et al. · Future Internet (2025) | TGRS Research Map | TGRS