AIMC Topic: Adult

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Image Segmentation and Machine Learning for Detection of Abdominal Free Fluid in Focused Assessment With Sonography for Trauma Examinations: A Pilot Study.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
The objective of this pilot study was to test the feasibility of automating the detection of abdominal free fluid in focused assessment with sonography for trauma (FAST) examinations. Perihepatic views from 10 FAST examinations with positive results ...

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

NeuroImage. Clinical
Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clin...

ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

Journal of medical systems
The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predic...

Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning.

PloS one
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...

A Concept-Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Identifying predictors of kidney disease progression is critical toward the development of strategies to prevent kidney failure. Clinical notes provide a unique opportunity for big data approaches to identify novel risk fac...

A robot-based behavioural task to quantify impairments in rapid motor decisions and actions after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke can affect our ability to perform daily activities, although it can be difficult to identify the underlying functional impairment(s). Recent theories highlight the importance of sensory feedback in selecting future motor actions. T...

Support vector machine classification of arterial volume-weighted arterial spin tagging images.

Brain and behavior
INTRODUCTION: In recent years, machine-learning techniques have gained growing popularity in medical image analysis. Temporal brain-state classification is one of the major applications of machine-learning techniques in functional magnetic resonance ...

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BMC bioinformatics
BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in hum...

Effect of timing of hip extension assistance during loaded walking with a soft exosuit.

Journal of neuroengineering and rehabilitation
BACKGROUND: Recent advances in wearable robotic devices have demonstrated the ability to reduce the metabolic cost of walking by assisting the ankle joint. To achieve greater gains in the future it will be important to determine optimal actuation par...

Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

Computational intelligence and neuroscience
We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obt...