Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looki...
BACKGROUND: The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology...
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 ...
To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, th...
International journal of clinical practice
Dec 11, 2020
PURPOSE: Some patients who undergo robot-assisted laparoscopic radical prostatectomy (RARP) continue to experience long-term urinary incontinence (UI). This study aimed to evaluate easily obtainable factors that can predict long-term UI following RAR...
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...
Recognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is ch...
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