This study aims to present the stages related to the use of machine learning algorithms for predictive analyses in health. An application was performed in a database of elderly residents in the city of São Paulo, Brazil, who participated in the Healt...
A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other slee...
Journal of neuroengineering and rehabilitation
Jul 29, 2019
BACKGROUND: Balance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effects on balance among patients with stroke, it remains unclear whether such training is superior to con...
BMC medical informatics and decision making
Jul 29, 2019
BACKGROUND: Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard to understand and trust these complex models due to the lack of intuition and explanation of their pr...
PURPOSE OF REVIEW: The promise of artificial intelligence (AI) in medicine has been widely theorized over the past couple of decades. It has only been with technological advances over the past few years that physicians and computer scientists have st...
AIM: To compare the efficacy of computed tomography (CT) texture analysis and conventional evaluation by radiologists for differentiation between large adrenal adenomas and carcinomas.
The Journal of asthma : official journal of the Association for the Care of Asthma
Jul 26, 2019
To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and allied-conditions (COPDAC) using a multi domain analysis of socio-ecological, clinical, and demographic domains. This is a retrospective case-risk-co...
Diagnostic and interventional imaging
Jul 26, 2019
PURPOSE: The purpose of this study was to report procedures developed to annotate abdominal computed tomography (CT) images from subjects without pancreatic disease that will be used as the input for deep convolutional neural networks (DNN) for devel...
BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of mortality in children, but the accurate prediction of outcomes at the point of admission remains very challenging. Admission laboratory results are a promising potential source of ...
Recently, there has been a proliferation of methods investigating functional connectivity as a biomarker for mental disorders. Typical approaches include massive univariate testing at each edge or comparisons of network metrics to identify differing ...
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