Research overview
The text below is the source article’s original abstract under a verified reuse license. cc by
Abstract Background AI is used in analysis, treatment planning, surgical and surgical neuroscience, psychiatry, and neurosurgery. However, the system may cause misdiagnosis or damage to gain knowledge of faults. Methods We systematically searched PubMed, Scopus, and IEEE Xplore (2018–2026) for authentic research evaluating AI for scientific standards. We extracted the gain metric and the error type. Results Seventy-nine studies achieved inclusion (32 neurology, 28 psychiatry, 19 neurosurgery). Benefits included faster lesion segmentation, improved schizophrenia classification, and improved brain tumor dissection rates. Errors occurred in 44% of studies: pediatric epilepsy AI missed 22% of lesions; Disappointment towards lost measure across all ethnic institutions; spine AI failed in osteotomy (9% error); Parkinson’s scans showed racial bias. Loss blankets do not frequent surgery, unnecessary capsules, and revision surgery. Discussion Errors cluster in underrepresented firms and edge cases. Mitigation requires fairness audits and assessments of uncertainty. Conclusion AI offers real benefits but feared by strict error tracking. Recommendations : External Authentication, Real-Time Error Monitoring, and Human Monitoring for High Threat Options.
Scientific assessment
Research question
Assess the question within the original study’s scope.
Methods & sample
Check the source article for study design and sample details.
Key findings
An editorially approved findings summary is not yet published for this record.
Limitations
Generalizability, bias and clinical meaning require separate assessment.
Methods, samples and clinical conclusions are not inferred from bibliographic metadata.