BACKGROUND: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess...
Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accurately than point-score tools. In patients with sepsis, however, the timing and scope of sepsis interventions relative to an advanced EWS alert are not wel...
Journal of X-ray science and technology
Jan 1, 2020
OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated dete...
BACKGROUND: Because Alzheimer's Disease (AD) has very complicated pattern changes, it is difficult to evaluate it with a specific factor. Recently, novel machine learning methods have been applied to solve limitations.
Journal of computer assisted tomography
Jan 1, 2020
OBJECTIVE: The aim of this study was to evaluate the diagnostic ability of support vector machine (SVM) for early breast cancer (BC) using dedicated breast positron emission tomography (dbPET).
BACKGROUND: Efforts to identify important risk factors for cognitive impairment and dementia have to date mostly relied on meta-analytic strategies. A comprehensive empirical evaluation of these risk factors within a single study is currently lacking...
BACKGROUND: Machine learning (ML) is a promising technique for patient-specific prediction of mild cognitive impairment (MCI) and dementia development. Neuropsychiatric symptoms (NPS) might improve the accuracy of ML models but have barely been used ...
Facial plastic surgery & aesthetic medicine
Jan 1, 2020
Quantitative assessment of facial function is challenging, and subjective grading scales such as House-Brackmann, Sunnybrook, and eFACE have well-recognized limitations. Machine learning (ML) approaches to facial landmark localization carry great cl...
BACKGROUND: The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and also would be responsive to the therapeutic intervention being studied (i.e., drug arm). ...
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