… The first analysis distinguished between malignant versus … are in the differential, in this
‘growths’ subgroup analysis, we … Similar trends were observed when restricting the analysis to …

… -analysis to evaluate the diagnostic value of radiomics-based machine learning (ML) for
PD. … During this meta-analysis, we discussed the differential diagnostic value of radiomics-based …

… We previously reported the utility of AI analysis for the diagnosis of malignancy in
intraductal papillary mucinous neoplasm (IPMN), and we believe AI may be able to diagnose …

… diagnosis [15]. In this study, we demonstrated that the use of deep learning to carry out image
analysis … That analysis efficiently distinguished the PMNs and monocytes found in patients …

… Machine Learning models to improve the differential diagnosis between … We performed a
two-stage kinematic analysis, first to … Machine Learning models for the differential diagnosis of …

… The performance analysis of our model was mainly developed around this dataset. (2)
Two-stage test set with 440 samples that had only the text and numerical features required for the …

… In this regard, we propose an innovative and effective technique to analyze medical images
for clinical diagnosis of PD. In essence, it is based on combination of two machine learning …

… These funders were not involved in the study design, collection, analysis, interpretation of
data, the writing of this article or the decision to submit it for publication. Moreover, this study …

… differential diagnosis) and prediction of treatment response [33]. Lastly, ML could offer a tool
to analyze … Given the tremendous development of ML approaches to analyze data regarding …

… In this study, we used a computer-assisted diagnosis (CAD) system with deep learning
analysis of EUS images (EUS-CAD) and assessed its ability to differentiate GI stromal tumors (…