AI Medical Compendium Topic:
Severity of Illness Index

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Homecare Robots to Improve Health and Well-Being in Mild Cognitive Impairment and Early Stage Dementia: Results From a Scoping Study.

Journal of the American Medical Directors Association Sep 30, 2017
OBJECTIVES: This scoping study is the first step of a multiphase, international project aimed at designing a homecare robot that can provide functional support, track physical and psychological well-being, and deliver therapeutic intervention specifi...
Quality of Life Severity of Illness Index Interviews as Topic Cognitive Dysfunction Female Aged Male Risk Assessment Humans Prognosis Activities of Daily Living Early Diagnosis Caregivers Cohort Studies Home Care Services Treatment Outcome Patient Acceptance of Health Care Robotics New Zealand
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Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.

Journal of manipulative and physiological therapeutics Jul 21, 2017
OBJECTIVES: This study aimed to provide an empirical model of predicting low back pain (LBP) by considering the occupational, personal, and psychological risk factor interactions in workers population employed in industrial units using an artificial ...
Disability Evaluation Iran Occupational Health Psychology Middle Aged Severity of Illness Index Case-Control Studies Predictive Value of Tests Low Back Pain Industry Life Style Occupational Diseases Humans Neural Networks, Computer Female Risk Factors Adult Male
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Applying an artificial neural network model for developing a severity score for patients with hereditary amyloid polyneuropathy.

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis Jul 18, 2017
Hereditary (familial) amyloid polyneuropathy (FAP) is a systemic disease that includes a sensorimotor polyneuropathy related to transthyretin (TTR) mutations. So far, a scale designed to classify the severity of this disease has not yet been validate...
Humans Neural Networks, Computer Female Male Severity of Illness Index Amyloid Neuropathies, Familial Models, Biological Prealbumin Amino Acid Substitution Mutation, Missense
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Usability testing of a developed assistive robotic system with virtual assistance for individuals with cerebral palsy: a case study.

Disability and rehabilitation. Assistive technology Jul 4, 2017
This paper presents a novel application of an assistive robotic system with virtual assistance to enhance manual performance of individuals with cerebral palsy. Cerebral palsy affects one's voluntary motor movements resulting in limited opportunities...
Severity of Illness Index Humans User-Computer Interface Physical Therapy Modalities Female Cerebral Palsy Robotics Middle Aged Movement Hand
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Diagnosis of Alzheimer's Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network.

Journal of healthcare engineering Jun 21, 2017
. Error-free diagnosis of Alzheimer's disease (AD) from healthy control (HC) patients at an early stage of the disease is a major concern, because information about the condition's severity and developmental risks present allows AD sufferer to take p...
Wavelet Analysis Magnetic Resonance Imaging Sensitivity and Specificity Principal Component Analysis Case-Control Studies Humans Alzheimer Disease Male Pattern Recognition, Automated Middle Aged Neural Networks, Computer Severity of Illness Index Algorithms Brain Diagnosis, Computer-Assisted Dementia Image Processing, Computer-Assisted Female Reproducibility of Results Aged Aged, 80 and over
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Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

Methods of information in medicine Jun 7, 2017
OBJECTIVES: The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic va...
Sleep Apnea, Obstructive Polysomnography Humans Male Middle Aged Machine Learning Female Severity of Illness Index Algorithms Aged Cohort Studies Young Adult Adult
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Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

Journal of biomedical informatics May 12, 2017
BACKGROUND: The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes ou...
Humans Neural Networks, Computer Severity of Illness Index Neuropsychological Tests
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Flexion synergy overshadows flexor spasticity during reaching in chronic moderate to severe hemiparetic stroke.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology May 12, 2017
OBJECTIVE: Pharmaceutical intervention targets arm flexor spasticity with an often-unsuccessful goal of improving function. Flexion synergy is a related motor impairment that may be inadvertently neglected. Here, flexor spasticity and flexion synergy...
Humans Prospective Studies Female Aged Cross-Sectional Studies Male Middle Aged Paresis Stroke Muscle Spasticity Arm Severity of Illness Index Range of Motion, Articular Chronic Disease Movement Robotics Electromyography
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Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine.

PloS one May 4, 2017
To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in clinical practice. We apply a modern machine learning method, the support vector machine to establish a predicting model for the severity of OSA. The suppor...
Support Vector Machine Humans Male Sleep Apnea, Obstructive Anthropometry Female Middle Aged Adult Severity of Illness Index Models, Theoretical
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Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

Artificial intelligence in medicine Apr 27, 2017
BACKGROUND AND OBJECTIVES: Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE fram...
Learning Curve Area Under Curve Supervised Machine Learning Data Mining Observer Variation Electronic Health Records Reproducibility of Results Humans Severity of Illness Index Phenotype Time Factors
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