… explicit and certain than clinical symptoms. However, considering the obtained accuracy of
77%, the authors suggested that the proposed model might not fit for clinical application but it …

… As a result of the clinical system at our institution, all patients who meet clinical trigger …
In this manuscript, the authors demonstrate that deep learning techniques can improve the …

… based on symptom data and specific clinical parameters. … effect of each feature like
symptoms in our case on survival … In this study, a clinical dataset for COVID-19 patients is used […

… Although further studies are required, we believe the CAD system may assist with timely
clinical decision making in those situations. In this situation, patients with positive radiographs …

… We thoroughly analyzed clinical data of this patient and found … clinical symptoms for DLBCL.
To us, it was questionable whether this patient really had DLBCL. Based on the symptoms …

… maxillary sinuses had no clinical symptoms in the sinuses, but … Patients with maxillary sinusitis
had clinical symptoms such … maxillary sinuses, had clinical symptoms with cheek swelling, …

… clinical presentation has not met the urgent clinical need so far. We aimed to establish a
deep learning (DL) model based on quantitative computed tomography (CT) and initial clinical …

… CT image set using a 3D deep learning model. These separated … The deep learning models
established in this study were … supplementary diagnostic method for frontline clinical doctors. …

… clinical methods was possible, the deep learning model had comparable or better performance.
Conclusions and Relevance The deep learning … patients with clinical symptoms of acute …

… ) is an infectious disease with first symptoms similar to the flu. … images, this paper investigates
deep learning methods for … In this context, training datasets, deep learning architectures …