AIMC Topic: Aged

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Contactless facial video recording with deep learning models for the detection of atrial fibrillation.

Scientific reports
Atrial fibrillation (AF) is often asymptomatic and paroxysmal. Screening and monitoring are needed especially for people at high risk. This study sought to use camera-based remote photoplethysmography (rPPG) with a deep convolutional neural network (...

Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.

Computational and mathematical methods in medicine
The research is aimed at investigating computed tomography (CT) image based on deep learning algorithm and the application value of ceramide glycosylation in diagnosing bladder cancer. The images of ordinary CT detection were improved. In this study,...

Identification of an early-stage Parkinson's disease neuromarker using event-related potentials, brain network analytics and machine-learning.

PloS one
OBJECTIVE: The purpose of this study is to explore the possibility of developing a biomarker that can discriminate early-stage Parkinson's disease from healthy brain function using electroencephalography (EEG) event-related potentials (ERPs) in combi...

Insurance payment for artificial intelligence technology: Methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment.

The neuroradiology journal
The first ever insurance reimbursement for an artificial intelligence (AI) system, which expedites triage of acute stroke, occurred in 2020 when the Centers for Medicare and Medicaid Services (CMS) granted approval for a New Technology Add-on Payment...

A pilot study of machine-learning based automated planning for primary brain tumours.

Radiation oncology (London, England)
PURPOSE: High-quality radiotherapy (RT) planning for children and young adults with primary brain tumours is essential to minimize the risk of late treatment effects. The feasibility of using automated machine-learning (ML) to aid RT planning in this...

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

The Lancet. Digital health
BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aim...

Robotic transabdominal retromuscular rectus diastasis (r-TARRD) repair: a new approach.

Hernia : the journal of hernias and abdominal wall surgery
PURPOSE: The aim of this study is to present our innovative robotic approach for the treatment of rectus diastasis with concurrent primary or incisional ventral hernias.

How Does Age Affect Urinary Continence following Robot-Assisted Radical Prostatectomy? A Prospective Multi-Institutional Study Using Independently Collected, Validated Questionnaires.

The Journal of urology
PURPOSE: Robot-assisted radical prostatectomy (RARP) is associated with poorer postoperative urinary continence in older men. However, published studies reporting conflicting results have design limitations with insufficient data at the extremes of a...

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BMC anesthesiology
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...

Disease Progression Detection via Deep Sequence Learning of Successive Radiographic Scans.

International journal of environmental research and public health
The highly rapid spread of the current pandemic has quickly overwhelmed hospitals all over the world and motivated extensive research to address a wide range of emerging problems. The unforeseen influx of COVID-19 patients to hospitals has made it in...