AIMC Topic: Middle Aged

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Discovering and identifying New York heart association classification from electronic health records.

BMC medical informatics and decision making Jul 23, 2018
BACKGROUND: Cardiac Resynchronization Therapy (CRT) is an established pacing therapy for heart failure patients. The New York Heart Association (NYHA) class is often used as a measure of a patient's response to CRT. Identifying NYHA class for heart f...
Heart Failure Cardiac Resynchronization Therapy New York Middle Aged Machine Learning Disease Progression Electronic Health Records Treatment Outcome Female Natural Language Processing Aged Male Humans
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Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

Physiological measurement Jul 23, 2018
OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupe...
Machine Learning Female Young Adult Adult Male Humans Neural Networks, Computer Exercise Therapy Middle Aged Healthy Volunteers Support Vector Machine Shoulder Monitoring, Physiologic Physical Therapy Modalities Signal Processing, Computer-Assisted Computers, Handheld Patient Compliance
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A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging Jul 21, 2018
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...
Databases, Factual Humans Prospective Studies Retrospective Studies Neural Networks, Computer Aged Signal Processing, Computer-Assisted Adult ROC Curve Female Observer Variation Male Image Processing, Computer-Assisted Fourier Analysis Middle Aged Support Vector Machine Deep Learning Magnetic Resonance Imaging
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A Prediction Model Using Machine Learning Algorithm for Assessing Stone-Free Status after Single Session Shock Wave Lithotripsy to Treat Ureteral Stones.

The Journal of urology Jul 20, 2018
PURPOSE: The aim of this study was to develop and validate a decision support model using a machine learning algorithm to predict treatment success after single session shock wave lithotripsy in ureteral stone cases.
Middle Aged Treatment Outcome Ureteral Calculi Lithotripsy Algorithms Decision Support Techniques Computer Simulation Prognosis Retrospective Studies Humans Tomography, X-Ray Computed Machine Learning Female Adult Male
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Postoperative bleeding risk prediction for patients undergoing colorectal surgery.

Surgery Jul 20, 2018
BACKGROUND: There is limited consensus regarding risk factors for postoperative bleeding. The objective of this work was to investigate the capability of machine learning techniques in combination with practice-based longitudinal electronic medical r...
Aged Adult Male Middle Aged Risk Assessment Postoperative Hemorrhage Colorectal Surgery Humans Machine Learning Retrospective Studies Electronic Health Records Female
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On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

European journal of radiology Jul 20, 2018
PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T-W/FLAIR images. Most studies involving differentiation between vasog...
Image Processing, Computer-Assisted Glioma Support Vector Machine Magnetic Resonance Imaging Humans Diagnosis, Differential Brain Brain Neoplasms Retrospective Studies Brain Edema Male Postoperative Period Female Middle Aged Preoperative Care Aged ROC Curve Young Adult Adult
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Predicting hospital admission at emergency department triage using machine learning.

PloS one Jul 20, 2018
OBJECTIVE: To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.
Patient Discharge Patient Admission Male Middle Aged Humans Models, Statistical Machine Learning Female Triage Adult Emergency Service, Hospital
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Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.

The oncologist Jul 17, 2018
BACKGROUND: 1p/19q-codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent gen...
Male Middle Aged Cohort Studies DNA Copy Number Variations Oligodendroglioma Humans Machine Learning Prognosis Female
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Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.

Sensors (Basel, Switzerland) Jul 17, 2018
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for ...
Male Middle Aged Photoplethysmography Constriction, Pathologic Arteriovenous Fistula Algorithms Female Aged Aged, 80 and over Humans Neural Networks, Computer
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Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 16, 2018
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...
Somatosensory Cortex Magnetic Resonance Imaging Spondylitis, Ankylosing Brain Mapping Sex Characteristics Rest Connectome Gyrus Cinguli Thalamus Chronic Pain Adult Biological Clocks Humans Male Machine Learning Middle Aged Female Functional Neuroimaging Young Adult Adolescent
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