ReviewDiagnostics (Basel, Switzerland)2022
Applications of Explainable Artificial Intelligence in Diagnosis and Surgery.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers, 4 of them syntheses that pooled 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.
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.
Who cites it
101 citing papers in PubMed, 4 syntheses or guidelines pooled it, 333 citations in OpenAlex.
- Explainable artificial intelligence (XAI) in medical imaging: a systematic review of techniques, applications, and challenges.BMC medical imaging · 2026Pooled it
- Artificial intelligence diagnostic performance in image-based vulnerable carotid plaque detection: a systematic review and meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- A systematic review of machine learning models for management, prediction and classification of ARDS.Respiratory research · 2024Pooled it
- Image-based AI diagnostic performance for fatty liver: a systematic review and meta-analysis.BMC medical imaging · 2023Pooled it
- Explainable SHAP-space fall risk profiling from electronic health records for inpatient prevention planning.npj health systems · 2026Article
- Methodological Pluralism in Surgical Evidence: from Concept to Practice.Surgery in practice and science · 2026Review
- Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.Journal of imaging · 2026Review
- Smart sensing the spectrum: cutting-edge biosensor and biomarker approaches for early autism detection.Metabolic brain disease · 2026Review
- An interpretable whole-stream video based deep learning framework for surgical skill assessment of basic procedural elements.International journal of surgery (London, England) · 2026Article
- Automatic detection of multi-site oral squamous cell carcinoma based on privacy-preserving federated learning.BMC oral health · 2026Article
- Artificial intelligence in clinical physiology: System-wise applications in diagnostics, monitoring, and medical education.Journal of family medicine and primary care · 2026Article
- Artificial intelligence to investigate metabolomics data for precision medicine.Metabolomics : Official journal of the Metabolomic Society · 2026Review
- Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.Gut and liver · 2026Review
- Harnessing artificial intelligence for the assessment of liver fibrosis and steatosisWorld journal of gastroenterology · 2026Review
- A knowledge-based Bayesian network reveals shared prediction errors with physicians in Gamma Knife radiosurgery.Frontiers in neuroscience · 2026Article
- Explainable artificial intelligence (XAI) in schizophrenia: enhancing transparency in clinical decision-making.Frontiers in systems biology · 2026Review
- Mortality prediction with adjuvant tamoxifen in breast cancer: Machine learning-integrated explainable artificial intelligence and Bayesian model results.ADMET & DMPK · 2026Article
- Beyond the black box in healthcare operations: a structured literature review and governance framework for explainable AI in clinical process intelligence systems.Frontiers in artificial intelligence · 2026Review
- Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients.BMC musculoskeletal disorders · 2025Article
- Unveiling the Algorithm: The Role of Explainable Artificial Intelligence in Modern Surgery.Healthcare (Basel, Switzerland) · 2025Review
41 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
In recent years, artificial intelligence (AI) has shown great promise in medicine. However, explainability issues make AI applications in clinical usages difficult. Some research has been conducted into explainable artificial intelligence (XAI) to overcome the limitation of the black-box nature of AI methods. Compared with AI techniques such as deep learning, XAI can provide both decision-making and explanations of the model. In this review, we conducted a survey of the recent trends in medical diagnosis and surgical applications using XAI. We have searched articles published between 2019 and 2021 from PubMed, IEEE Xplore, Association for Computing Machinery, and Google Scholar. We included articles which met the selection criteria in the review and then extracted and analyzed relevant information from the studies. Additionally, we provide an experimental showcase on breast cancer diagnosis, and illustrate how XAI can be applied in medical XAI applications. Finally, we summarize the XAI methods utilized in the medical XAI applications, the challenges that the researchers have met, and discuss the future research directions. The survey result indicates that medical XAI is a promising research direction, and this study aims to serve as a reference to medical experts and AI scientists when designing medical XAI applications.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.