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Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Scientific reports
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...

A CNN-aided method to predict glaucoma progression using DARC (Detection of Apoptosing Retinal Cells).

Expert review of molecular diagnostics
BACKGROUND: A key objective in glaucoma is to identify those at risk of rapid progression and blindness. Recently, a novel first-in-man method for visualising apoptotic retinal cells called DARC (Detection-of-Apoptosing-Retinal-Cells) was reported. T...

An Open-Source Computer Vision Tool for Automated Vocal Fold Tracking From Videoendoscopy.

The Laryngoscope
OBJECTIVES: Contemporary clinical assessment of vocal fold adduction and abduction is qualitative and subjective. Herein is described a novel computer vision tool for automated quantitative tracking of vocal fold motion from videolaryngoscopy. The po...

Development of machine learning-based preoperative predictive analytics for unruptured intracranial aneurysm surgery: a pilot study.

Acta neurochirurgica
BACKGROUND: The decision to treat unruptured intracranial aneurysms (UIAs) or not is complex and requires balancing of risk factors and scores. Machine learning (ML) algorithms have previously been effective at generating highly accurate and comprehe...

Working memory load-dependent changes in cortical network connectivity estimated by machine learning.

NeuroImage
Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to cha...

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

Gastroenterology
BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems allow for real-time computer-aided detection (CADe) of polyps with high accuracy. ...

Segmenting nailfold capillaries using an improved U-net network.

Microvascular research
To assess the microcirculation in a patient's capillaries, clinicians often use the valuable and non-invasive diagnostic tool of nailfold capillaroscopy (NC). In particular, evaluating the images that result from NC is particularly important for diag...

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.

BMC public health
BACKGROUND: Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine lea...

Deep learning-based monocular placental pose estimation: towards collaborative robotics in fetoscopy.

International journal of computer assisted radiology and surgery
PURPOSE: Twin-to-twin transfusion syndrome (TTTS) is a placental defect occurring in monochorionic twin pregnancies. It is associated with high risks of fetal loss and perinatal death. Fetoscopic elective laser ablation (ELA) of placental anastomoses...