The estimation of central choroidal thickness from colour fundus images can improve disease detection. We developed a deep learning method to estimate central choroidal thickness from colour fundus images at a single institution, using independent da...
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Mar 28, 2024
OBJECTIVE: The analysis of surgical videos using artificial intelligence holds great promise for the future of surgery by facilitating the development of surgical best practices, identifying key pitfalls, enhancing situational awareness, and dissemin...
Hong Kong medical journal = Xianggang yi xue za zhi
Mar 28, 2024
INTRODUCTION: This study compared the performance of the artificial neural network (ANN) model with the Acute Physiologic and Chronic Health Evaluation (APACHE) II and IV models for predicting hospital mortality among critically ill patients in Hong ...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Mar 27, 2024
Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis severity is the Cobb angle which is measured on radiographs by human specialists, carrying interobse...
BACKGROUND: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.
OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.
OBJECTIVES: This study aimed to develop machine learning models for risk prediction of continuous renal replacement therapy (CRRT) following coronary artery bypass grafting (CABG) surgery in intensive care unit (ICU) patients.
PURPOSE: To distinguish malignant and benign bowel wall thickening (BWT) by using computed tomography (CT) texture features based on machine learning (ML) models and to compare its success with the clinical model and combined model.
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