AIMC Topic: Aged, 80 and over
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Can AI Help Reduce Disparities in General Medical and Mental Health Care?
AMA journal of ethics
Feb 1, 2019
BACKGROUND: As machine learning becomes increasingly common in health care applications, concerns have been raised about bias in these systems' data, algorithms, and recommendations. Simply put, as health care improves for some, it might not improve ...
Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2.
JAMA network open
Feb 1, 2019
IMPORTANCE: As currently used, microperimetry is a burdensome clinical testing modality for testing retinal sensitivity requiring long testing times and trained technicians.
A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.
Journal of medical systems
Feb 1, 2019
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Argentinian multicenter study on urinary tract infections due to Streptococcus agalactiae in adult patients.
Journal of infection in developing countries
Jan 31, 2019
INTRODUCTION: Streptococcus agalactiae (group B streptococcus, GBS) is a recognized urinary pathogen both in males and pregnant or non-pregnant women. Data regarding GBS serotypes recovered from urinary tract infections (UTIs) are scarce. The aim of ...
A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.
American journal of ophthalmology
Jan 26, 2019
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...
Visual Field Tests
Humans
Male
Female
Tomography, Optical Coherence
Optic Nerve Diseases
Middle Aged
Aged
Nerve Fibers
Photography
Deep Learning
Aged, 80 and over
Optic Disk
Glaucoma, Open-Angle
Vision Disorders
Algorithms
Retinal Ganglion Cells
Cross-Sectional Studies
Area Under Curve
Retrospective Studies
Bruch Membrane
Intraocular Pressure
Visual Fields
Prediction of skin dose in low-kV intraoperative radiotherapy using machine learning models trained on results of in vivo dosimetry.
Medical physics
Jan 25, 2019
PURPOSE: The purpose of this study was to implement a machine learning model to predict skin dose from targeted intraoperative (TARGIT) treatment resulting in timely adoption of strategies to limit excessive skin dose.
Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies.
EBioMedicine
Jan 20, 2019
BACKGROUND: Early diagnosis of skin cancer lesions by dermoscopy, the gold standard in dermatological imaging, calls for a diagnostic upscale. The aim of the study was to improve the accuracy of dermoscopic skin cancer diagnosis through use of novel ...
Machine learning as a supportive tool to recognize cardiac arrest in emergency calls.
Resuscitation
Jan 18, 2019
BACKGROUND: Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. We examined whether a machine lear...
A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.
NeuroImage
Jan 14, 2019
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to pr...
Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning.
BMC medical informatics and decision making
Jan 8, 2019
BACKGROUND: Machine-learning classifiers mostly offer good predictive performance and are increasingly used to support shared decision-making in clinical practice. Focusing on performance and practicability, this study evaluates prediction of patient...
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