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Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.

Translational vision science & technology
PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images.

Semantic and structural image segmentation for prosthetic vision.

PloS one
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...

Robotic perineal radical prostatectomy in a patient with a pre-existing three piece inflatable penile prosthesis.

Aktuelle Urologie
Radical prostatectomy (RP) is the primary and standard treatment for localized prostate cancer. As in many surgical procedures, RP can now be accomplished through minimally invasive methods. RP in a patient with a pre-existing 3-piece inflatable peni...

Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identi...

Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Pancreatic cancer remains a disease of high mortality despite advanced diagnostic techniques. Mucins (MUC) play crucial roles in carcinogenesis and tumor invasion in pancreatic cancers. MUC1 and MUC4 expression are related to the aggressive ...

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

Acta neurologica Belgica
The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on mobility, activities of daily living (ADLs), and quality of life (QoL) in stroke rehabilitation. Fifty-one stroke patients randomly assigned to Group 1...

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Radiology
Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with extensive infarction are unlikely to benefit from thrombolysis or t...

Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Stroke
Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging to identify patients within the reco...

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

Journal of neuroengineering and rehabilitation
BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, vari...

Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers.

American journal of surgery
INTRODUCTION: In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.