… None of the comorbidities and symptoms (except diarrhea) were among the top predictors
in our cohort although some comorbidities and symptoms were significantly different between …

… considerably improve chances for curbing symptoms and the underlying disease; … symptoms
is challenging and resource demanding. Current approaches are mainly based on clinical …

… deep learning models for COVID-19 imaging as clinical decision support tools could be a
promising approach for leveraging AI capabilities in routine clinical … other clinical symptoms …

… We believe the application of deep learning to large clinical data sets can overcome this …
patients’ presenting symptoms. The application of deep learning to large clinical data sets can …

… CT in different clinical types according to days since initial symptoms at baseline CT. … In this
study, we evaluated the longitudinal changes of pneumonia severity in different clinical types …

… symptom information from notes. In our prior work, we developed a deep learning symptom
extraction model that was trained on the COVID-19 Annotated Clinical Text (CACT) Corpus.…

… clinical practice, less than 50% of the AD patients are diagnosed accurately for their pathology
and disease progression based on their clinical symptoms … including clinical symptoms 20 …

… We included all research articles in all languages that applied deep learning models for
clinical … Modeling and prediction of clinical symptom trajectories in Alzheimer’s disease using …

… following criteria: clinical symptoms, epidemiological history … CT images using a deep
learning method. This is a … Moreover, the high performance of the deep learning model …

… These results highlight once more how deep learning could have a profound impact on
clinical practice and on personalized medicine. However, it has to be noted that this is a …