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Factor enhanced DeepSurv: A deep learning approach for predicting survival probabilities in cirrhosis data.

Computers in biology and medicine
BACKGROUND: Over the years, various models, including both traditional and machine learning models, have been employed to predict survival probabilities for diverse survival datasets. The objective is to obtain models that provide more accurate estim...

Deep learning models for early and accurate diagnosis of ventilator-associated pneumonia in mechanically ventilated neonates.

Computers in biology and medicine
BACKGROUND: Early and accurate confirmation of critically ill neonates with a suspected diagnosis of ventilator-associated pneumonia (VAP) can optimize the therapeutic strategy and avoid unnecessary use of empirical antibiotics. We aimed to examine w...

Deep learning models for improving Parkinson's disease management regarding disease stage, motor disability and quality of life.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Motor diagnosis, monitoring and management of Parkinson's disease (PD) focuses mainly on observational methods and, clinical scales, resulting in a subjective evaluation. Inertial sensors combined with artificial intelligenc...

Feasibility exploration of myocardial blood flow synthesis from a simulated static myocardial computed tomography perfusion via a deep neural network.

Journal of X-ray science and technology
BACKGROUND:  Myocardial blood flow (MBF) provides important diagnostic information for myocardial ischemia. However, dynamic computed tomography perfusion (CTP) needed for MBF involves multiple exposures, leading to high radiation doses.

Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images.

Current medical science
OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.

Machine Learning-Aided Identification of Fecal Extracellular Vesicle microRNA Signatures for Noninvasive Detection of Colorectal Cancer.

ACS nano
Colorectal cancer (CRC) remains a formidable threat to human health, with considerable challenges persisting in its diagnosis, particularly during the early stages of the malignancy. In this study, we elucidated that fecal extracellular vesicle micro...

Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair.

Journal of the American Heart Association
BACKGROUND: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remai...

Physician Perspectives on Ambient AI Scribes.

JAMA network open
IMPORTANCE: Limited qualitative studies exist evaluating ambient artificial intelligence (AI) scribe tools. Such studies can provide deeper insights into ambient AI implementations by capturing lived experiences.

Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...