AIMC Topic: Aged

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Artificial Neural Network Learns Clinical Assessment of Spasticity in Modified Ashworth Scale.

Archives of physical medicine and rehabilitation Apr 19, 2019
OBJECTIVE: To propose an artificial intelligence (AI)-based decision-making rule in modified Ashworth scale (MAS) that draws maximum agreement from multiple human raters and to analyze how various biomechanical parameters affect scores in MAS.
Humans Middle Aged Aged Neurologic Examination Elbow Joint Aged, 80 and over Neural Networks, Computer Brain Diseases Adult Prospective Studies Hemiplegia Biomechanical Phenomena Female Muscle Spasticity Male
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Automated and accurate quantification of subcutaneous and visceral adipose tissue from magnetic resonance imaging based on machine learning.

Magnetic resonance imaging Apr 18, 2019
Accurate measuring of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) is vital for the research of many diseases. The localization and quantification of SAT and VAT by computed tomography (CT) expose patients to harmful ionizing r...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Cluster Analysis Intra-Abdominal Fat Subcutaneous Fat Aged Aged, 80 and over Adult Male Middle Aged Humans Machine Learning Female Reproducibility of Results
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Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

Journal of cellular and molecular medicine Apr 18, 2019
BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival outcome and associations with differentially expressed Genes (RNA Sequencing) in groups of glioblastoma multiforme (GBM) patients.
Glioblastoma Radiographic Image Interpretation, Computer-Assisted Adolescent Machine Learning Brain Neoplasms ROC Curve Algorithms Male Genomics Prognosis Middle Aged Gene Expression Regulation, Neoplastic Female Humans Gene Expression Profiling Magnetic Resonance Imaging Aged Transcriptome Aged, 80 and over Young Adult Adult Survival Rate Biomarkers, Tumor
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Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
Models, Statistical Radiotherapy Radiation Pneumonitis Middle Aged ROC Curve Lung Neoplasms Nomograms Carcinoma, Non-Small-Cell Lung Humans Machine Learning Cytokines Prospective Studies Female Aged Biomarkers, Tumor Male
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A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

Osteoarthritis and cartilage Apr 16, 2019
OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progressi...
Humans Machine Learning Databases, Factual Aged Biomarkers Menisci, Tibial United States Male Congresses as Topic Female Middle Aged Pain Measurement National Institutes of Health (U.S.) Disease Progression Osteoarthritis, Knee Biological Variation, Population Severity of Illness Index Collagen Type II Cartilage, Articular
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Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia.

International journal of geriatric psychiatry Apr 15, 2019
OBJECTIVES: The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (MCI) to dementia. We used traditional and machine learning (ML) techniques to compare converter and n...
Humans Machine Learning Disease Progression Cognitive Dysfunction Dementia Longitudinal Studies Predictive Value of Tests Cognitive Reserve Female Aged Aged, 80 and over Male Middle Aged
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Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.

Scientific reports Apr 15, 2019
We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n...
Humans Retrospective Studies Feasibility Studies Image Interpretation, Computer-Assisted Datasets as Topic Hematologic Diseases Support Vector Machine Female Magnetic Resonance Imaging Aged Radiologists Male Lumbar Vertebrae Middle Aged Bone Marrow ROC Curve
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Machine learning performance in a microbial molecular autopsy context: A cross-sectional postmortem human population study.

PloS one Apr 15, 2019
BACKGROUND: The postmortem microbiome can provide valuable information to a death investigation and to the human health of the once living. Microbiome sequencing produces, in general, large multi-dimensional datasets that can be difficult to analyze ...
Adolescent DNA, Archaeal Time Factors Young Adult DNA, Bacterial Humans Microbiota Machine Learning RNA, Ribosomal, 16S Autopsy Female Adult Sequence Analysis, DNA High-Throughput Nucleotide Sequencing Aged Cross-Sectional Studies Postmortem Changes Aged, 80 and over Male Datasets as Topic Middle Aged
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Machine Learning Analysis of Matricellular Proteins and Clinical Variables for Early Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Molecular neurobiology Apr 13, 2019
Although delayed cerebral ischemia (DCI) is a well-known complication after subarachnoid hemorrhage (SAH), there are no reliable biomarkers to predict DCI development. Matricellular proteins (MCPs) have been reported relevant to DCI and expected to b...
Humans Machine Learning Subarachnoid Hemorrhage Brain Ischemia Intracranial Aneurysm Algorithms Female Aged Male Models, Biological
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Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade.

Journal of the American College of Radiology : JACR Apr 12, 2019
PURPOSE: Osteoporosis is an underdiagnosed condition despite effective screening modalities. Dual-energy x-ray absorptiometry (DEXA) screening, although recommended in clinical guidelines, remains markedly underutilized. In contrast to DEXA, CT utili...
Deep Learning Lumbar Vertebrae Absorptiometry, Photon Humans Aged Computer Simulation Aged, 80 and over Bone Density Sensitivity and Specificity Osteoporosis Male Tomography, X-Ray Computed Middle Aged Female
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