… severity: (1) mild form: mild clinical symptoms without chest CT imaging signs of viral
pneumonia; (2) regular form: fever and respiratory symptoms with chest CT imaging signs of viral …

… learning step. Finally, the model begins a classification and prediction process with a fully
connected network formed of several classifiers. Deep learning … and effective clinical decision …

… In this experiment, we adopt patients with mild symptoms and without malignant … with deep
learning features, we replace the clinical features extracted by MLP with the selected clinical …

… Advancements in the field of machine learning aim to make informed predictions that
replace the burden of lengthy clinical interviews with rapid processing of patient data. A …

… whether momentary anxiety symptoms can be accurately … deep learning models to
predict future anxiety symptoms among a sample reporting clinical anxiety disorder symptoms. …

… The clinical protocols and research ethics are approved by the respective local institutional
ethics … Clinical data was collected for this study by healthcare professionals. Table I, Fig. 4 …

… clinical usability. We defined as our goal to build an hybrid machine learning/deep learning
severity predictive model that can act as an auxiliary tool for patient risk assessing in clinical …

… These limitations can be avoided by applying machine and deep learning to the classification
process. We developed and refined various free-text machine and deep learning models …

… This study aimed to develop a deep-learning model and a risk-score system using clinical
variables … Demographics, chronic comorbidities, vital signs, symptoms and laboratory tests at …

… a CAD system based on deep learning to classify COVID-19 infection versus other atypical
and viral pneumonia diseases. We hypothesized that the deep learning method would help …