The role of explainable artificial intelligence in disease prediction: a systematic literature review and future research directions
Explainable Artificial Intelligence (XAI) enhances transparency and interpretability in AI models, which is crucial for trust and accountability in healthcare. A potential application of XAI is disease prediction using various data modalities. This study conducts a Systematic Literature Review (SLR) following the PRISMA protocol, synthesizing findings from 30 selected studies to examine XAI's evolving role in disease prediction. It explores commonly used XAI methods, such as Shapley Additive Exp
Record details
Published: 4 March 2025
Source: OpenAlex
Category: Research
Topics: Safety & alignment · Healthcare · Transparency
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Interpretable Clustering: A Survey
OpenAlex · 16 January 2026
Human in the loop artificial intelligence in healthcare: applications, outcomes, and implementation challenges
OpenAlex · 19 February 2026
Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
arXiv · 11 March 2026
Adoption and Effectiveness of AI-Based Anomaly Detection for Cross Provider Health Data Exchange
arXiv · 19 March 2026
Behavioural feasible set: Value alignment constraints on AI decision support
arXiv · 22 March 2026
A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health
arXiv · 13 April 2026
How to cite this record
ethics.ai (4 March 2025), “The role of explainable artificial intelligence in disease prediction: a systematic literature review and future research directions,” evidence record 9690, https://ethics.ai/record/9690 (originally published by OpenAlex).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.