Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general popu...
The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma (RCC) is an important issue because of its relationship with subsequent kidney dysfunction and high mortality. Herein we addressed whether machine learning...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jul 31, 2021
UNLABELLED: Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of cardiovascular ri...
BMC medical informatics and decision making
Jul 30, 2021
BACKGROUND: In medical diagnosis and clinical practice, diagnosing a disease early is crucial for accurate treatment, lessening the stress on the healthcare system. In medical imaging research, image processing techniques tend to be vital in analyzin...
BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on disease stage and histology is inadequate. For some individuals with early-stage epithelioid tumours, a good prognosis by current guidelines can progres...
The purpose of this study is to apply a machine learning approach to predict whether patients with burning mouth syndrome (BMS) respond to the initial approach and clonazepam therapy based on clinical data. Among the patients with the primary type of...
IEEE journal of biomedical and health informatics
Jul 27, 2021
OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jul 26, 2021
OBJECTIVES: Classifying the possibility of home discharge is important during stroke rehabilitation to support decision-making. There have been several studies on supervised machine learning algorithms, but only a few have compared the performance of...
There was an investigation of the auxiliary role of convolutional neural network- (CNN-) based magnetic resonance imaging (MRI) image segmentation algorithm in MRI image-guided targeted drug therapy of doxorubicin nanomaterials so that the value of d...
The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke....
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