… clinical data for early diagnose of AD and to prove that we make a comparison between
clinical data diagnose … 16 to compare with clinical data to perform the accuracy of early-disease …

… on clinical judgment suggest that experts are not extremely accurate in their diagnostic decisions
… -making contexts, clinicians can and should be replaced by these linear models so that …

… of artificial intelligence on clinical settings of glioma, with a relatively narrow range of
evaluated use cases. In conclusion, application of artificial intelligence technologies to clinical …

… CDSS has been applied in clinical diagnosis 11 , preventive care 12 , and chronic disease
management 13 , among others. It provides a proficient decision-making service to improve …

… Useful screening tools to precisely diagnose cancer, … clinical diagnostics[22]. The AI algorithms
are already developed with large data sets that show improved diagnostics than clinicians…

… From the results of the present prospective clinical study, it is assumed that the thyroid US
CAD system does not provide added diagnostic value for an experienced radiologist, as the …

Objective This study aimed to summarize the characteristics and methodological quality of
systematic reviews on the application of artificial intelligence (AI) in clinical diagnosis and …

… prognosis of CVDs are limited in clinical practice by the use of … clinicians better understand
the applications of AI in CVDs, this review summarizes studies relating to AI-based diagnosis…

… Integrating AI into healthcare holds excellent potential for improving disease diagnosis,
treatment selection, and clinical laboratory testing. AI tools can leverage large datasets and …

… key clinical features driving the diagnosis prediction. For each feature, we identified which
category of EHR clinical … impact of clinical features used in our diagnostic system allowed us to …