A review of explainable AI techniques and their evaluation in mammography for breast cancer screening DOI Creative Commons

Noora Shifa,

Moutaz Saleh, Younes Akbari

и другие.

Clinical Imaging, Год журнала: 2025, Номер unknown, С. 110492 - 110492

Опубликована: Май 1, 2025

Язык: Английский

The Role of Artificial Intelligence in Diagnostic Neurosurgery: A Systematic Review DOI
William Li, Armand Gumera, Shiv Surya

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 4, 2025

Abstract Background: Artificial intelligence (AI) is increasingly applied in diagnostic neurosurgery, enhancing precision and decision-making neuro-oncology, vascular, functional, spinal subspecialties. Despite its potential, variability outcomes necessitates a systematic review of performance applicability. Methods: A comprehensive search PubMed, Cochrane Library, Embase, CNKI, ClinicalTrials.gov was conducted from January 2020 to 2025. Inclusion criteria comprised studies utilizing AI for reporting quantitative metrics. Studies were excluded if they focused on non-human subjects, lacked clear metrics, or did not directly relate applications neurosurgery. Risk bias assessed using the PROBAST tool. This study registered PROSPERO, number CRD42025631040 26th, Results: Within 186 studies, neural networks (29%) hybrid models (49%) dominated. categorised into neuro-oncology (52.69%), vascular neurosurgery (19.89%), functional (16.67%), (11.83%). Median accuracies exceeded 85% most categories, with achieving high accuracy tumour detection, grading, segmentation. Vascular excelled stroke intracranial haemorrhage median AUC values 97%. Functional showed promising results, though sensitivity specificity underscores need standardised datasets validation. Discussion: The review’s limitations include lack data weighting, absence meta-analysis, limited collection timeframe, quality, risk some studies. Conclusion: AI shows potential improving across neurosurgical domains. Models used stroke, ICH, aneurysm conditions such as Parkinson’s disease epilepsy demonstrate results. However, sensitivity, specificity, further research model refinement ensure clinical viability effectiveness.

Язык: Английский

Процитировано

0

A review of explainable AI techniques and their evaluation in mammography for breast cancer screening DOI Creative Commons

Noora Shifa,

Moutaz Saleh, Younes Akbari

и другие.

Clinical Imaging, Год журнала: 2025, Номер unknown, С. 110492 - 110492

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0