Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learni...
Journal of medical imaging and radiation sciences
Dec 13, 2020
BACKGROUND: Artificial Intelligence (AI) is making a continuous progression into the field of Radiation Oncology in Canada and globally. While this field continues to evolve, there is no clear understanding about how radiation oncologists, radiation ...
In the recent era, a liver syndrome that causes any damage in life capacity is exceptionally normal everywhere throughout the world. It has been found that liver disease is exposed more in young people as a comparison with other aged people. At the p...
OBJECTIVES: To test contemporary rates and predictors of open conversion at minimally invasive partial nephrectomy (MIPN: laparoscopic or robotic partial nephrectomy).
OBJECTIVE: To investigate the feasibility of using deep learning image reconstruction (DLIR) to significantly reduce radiation dose and improve image quality in contrast-enhanced abdominal CT.
International journal of environmental research and public health
Dec 11, 2020
This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the prediction of metabolic syndrome (MetS) based on socioeconomic status and lifestyle factors. The data of 27,415 subjects who went through examinations...
In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develo...
The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactorial. The Massive Parallel Limitless-Arity Multiple-testing Procedure (MP-LAMP), which was developed to detect significant combinational risk factors com...
BMC medical informatics and decision making
Dec 10, 2020
BACKGROUND: Accurate prediction models for whether patients on the verge of a psychiatric criseis need hospitalization are lacking and machine learning methods may help improve the accuracy of psychiatric hospitalization prediction models. In this pa...
BACKGROUND: Although protective mechanical ventilation (MV) has been used in a variety of applications, lung injury may occur in both patients with and without acute respiratory distress syndrome (ARDS). The purpose of this study is to use machine le...
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