… A few studies have been conducted on osteoporosis diagnosis with image and clinical
covariates using DL. An artificial neural network model using clinical symptoms and image …

… those with COVID-19), 130 clinical symptoms (a series of symptoms including biochemical
and cellular analysis of blood and urine), as well as the clinical symptoms of SARS-CoV-2, …

… Nonetheless, in this work, we do include signs, which are symptoms that can be recorded
in a clinical setting. For a distinction of the classes, we refer to the Human Disease Ontology [ …

… blood pressure rate, and clinical symptoms. Distribution of the … Deep learning techniques
have played a significant role in … types of clinical applications using the deep learning framework…

… estimated lesion burden with clinical symptoms of the patients, ie, a rise of estimated
lesion burden was accompanied with relatively severe clinical symptoms. Figure 6 shows the …

… Research outcomes on COVID-19 confirmed cases, indicated that CT abnormalities, before
the appearance of clinical symptoms, may occur [8]. Asymptomatic patients typically have …

… method for clinical diagnosis of COVID-19 by combining the patient’s clinical symptoms and
… for quick diagnosis as early as possible in the clinical practice. It is also effectively helpful to …

… imaging and advanced deep learning methods is promising for clinical decision making and
have … , therefore, memory loss is one of the early symptoms of AD. The exact cause of AD is …

… together with encoded clinical data were input to the fully connected layer for classifying
liver tumors. Our deep learning model can accept clinical data as input. Clinical data was …

… -19 infectious period (defined as 7 days prior and 21 days after symptom onset) (figure 1A).
Before applying the deep learning framework, we inferred resting heart rate (RHR) from heart …