Systematic review reveals improvements in diagnostic efficiency through explainable AI in healthcare, indicating a path towards trust and compliance.
Key Points
The study aims to explore the role of explainable artificial intelligence (XAI) in enhancing clinical decision-making and patient safety in the medical field.
Conducted a systematic review of XAI in medical scenarios over the past five years.
Analyzed XAI solutions focusing on technical frameworks and clinical applications.
Investigated challenges including interpretability versus performance and standardization issues.
Found that XAI improves diagnostic efficiency and reduces medical errors.
Highlighted the importance of XAI in ensuring diagnosis and treatment safety.
Proposed collaboration between doctors and XAI for better decision-making.