Evidence map›Paper›PMID 41340890›Full record

ReviewComputational and structural biotechnology journal2025

Coalition of explainable artificial intelligence and quantum computing in precision medicine.

Soumyadeep Ray, Pronaya Bhattacharya, Ebrahim A Mattar, Abhishek Mukhopadhyay

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Soumyadeep RayDepartment of Biotechnology, Amity University, Newtown, Kolkata, 700135, West Bengal, India.
Pronaya BhattacharyaDepartment of Computer Science and Engineering, Amity University, Newtown, Kolkata, 700135, West Bengal, India.
Ebrahim A MattarRobotics and Cybernetics, College of Engineering, University of Bahrain, Bahrain.
Abhishek MukhopadhyayComputer Science and Engineering, Amity University, Newtown, Kolkata, 700135, West Bengal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning models and XAI techniques applied to drug discovery, disease diagnosis, patient monitoring and biomarker identification. We introduce a taxonomy of hybrid and quantum-explainable approaches, evaluate NISQ hardware and encoding constraints, and compare interpretability methods (SHAP, LIME, QSHAP, QLRP, TSBA). Two case studies (doxorubicin cardiotoxicity prediction and pre-symptomatic IBD flare forecasting) demonstrate hybrid variational-quantum pipelines wrapped with SHAP-based explanations. We identify practical barriers (noise, data encoding, regulation, privacy) and outline research directions to benchmark clinical quantum advantage and develop scalable, transparent QXAI frameworks. The survey aims to guide interdisciplinary efforts toward trustworthy, scalable quantum-enabled precision healthcare.

Indexed as

Explainable artificial intelligencePrecision medicineQuantum computingQuantum machine learning

Identifiers

PMID41340890
PMCPMC12671375

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.