AIMC Topic: Aged

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Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Scientific reports Sep 5, 2018
Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal...
Humans Machine Learning Support Vector Machine Parkinson Disease Alzheimer Disease Neuroimaging Positron-Emission Tomography Lewy Body Disease Fluorodeoxyglucose F18 Female Aged Aged, 80 and over Male Middle Aged
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RNA-seq analysis reveals different gene ontologies and pathways in rheumatoid arthritis and Kashin-Beck disease.

International journal of rheumatic diseases Sep 5, 2018
AIMS: To understand the pathogenesis of cartilage damage in Kashin-Beck disease (KBD) and rheumatoid arthritis (RA) which similar clinical symptoms.
Male Middle Aged Gene Regulatory Networks Arthritis, Rheumatoid Genetic Predisposition to Disease Humans Phenotype Female Aged Inflammation Mediators Cartilage Gene Ontology Kashin-Beck Disease Sequence Analysis, RNA Signal Transduction Databases, Genetic Proteoglycans RNA
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Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP) Sep 5, 2018
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.
Voice Quality Age Factors Aged Humans Symptom Assessment Glottis Supervised Machine Learning Adult Neural Networks, Computer Wounds and Injuries Sex Factors Male Algorithms Demography Smoking Retrospective Studies Vocal Cord Paralysis Middle Aged Alcohol Drinking Female Severity of Illness Index Voice Disorders Laryngeal Neoplasms
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Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

IEEE journal of biomedical and health informatics Sep 3, 2018
Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical su...
Parkinson Disease Multimodal Imaging Image Interpretation, Computer-Assisted Diffusion Tensor Imaging Humans Machine Learning Algorithms Brain Female Aged Male Middle Aged ROC Curve
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Performance of the deep convolutional neural network based magnetic resonance image scoring algorithm for differentiating between tuberculous and pyogenic spondylitis.

Scientific reports Sep 3, 2018
The purpose of this study was to evaluate the performance of the deep convolutional neural network (DCNN) in differentiating between tuberculous and pyogenic spondylitis on magnetic resonance (MR) imaging, compared to the performance of three skilled...
Neural Networks, Computer Algorithms Retrospective Studies Female Aged Adult Area Under Curve Humans Spine Supervised Machine Learning Image Interpretation, Computer-Assisted Spondylitis Male Tuberculosis, Osteoarticular Middle Aged ROC Curve Magnetic Resonance Imaging Diagnosis, Differential
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Robot-assisted gait training to reduce pusher behavior: A randomized controlled trial.

Neurology Aug 31, 2018
OBJECTIVE: To determine the effects of 2 weeks of intensive robot-assisted gait training (RAGT) on pusher behavior compared to nonrobotic physiotherapy (nR-PT).
Humans Female Aged Male Severity of Illness Index Treatment Outcome Follow-Up Studies Posture Cerebral Hemorrhage Robotics Perceptual Disorders Single-Blind Method Gait Brain Ischemia Therapy, Computer-Assisted Stroke Rehabilitation
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Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease.

PloS one Aug 31, 2018
Prognostic modelling is important in clinical practice and epidemiology for patient management and research. Electronic health records (EHR) provide large quantities of data for such models, but conventional epidemiological approaches require signifi...
Electronic Health Records Female Aged Aged, 80 and over Coronary Artery Disease Adult Humans Models, Biological Machine Learning Male Survival Analysis Prognosis Middle Aged Diagnosis, Computer-Assisted Cohort Studies Data Interpretation, Statistical
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A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation.

IEEE transactions on bio-medical engineering Aug 30, 2018
Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft-tissue contrast and lack of ionizing radiation. However, quantification of body composition requires an accurate se...
Whole Body Imaging Magnetic Resonance Imaging Fuzzy Logic Cluster Analysis Thigh Humans Body Composition Aged Algorithms Aged, 80 and over Brain Adult Middle Aged Image Processing, Computer-Assisted
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Diagnostic performance of real-time robotic arm-assisted F-FDG PET/CT-guided percutaneous biopsy in metabolically active abdominal and pelvic lesions.

European journal of nuclear medicine and molecular imaging Aug 30, 2018
PURPOSE: To evaluate the feasibility and diagnostic performance of F-FDG PET/CT-guided biopsy of abdominal and pelvic lesions with automated robotic arm (ARA) assistance.
Image-Guided Biopsy Male Middle Aged Adolescent Time Factors Abdomen Robotics Positron Emission Tomography Computed Tomography Pelvis Skin Feasibility Studies Fluorodeoxyglucose F18 Female Aged Aged, 80 and over Young Adult Adult Humans
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Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.

European radiology Aug 30, 2018
OBJECTIVE: To evaluate the performance of quantitative computed tomography (CT) texture analysis using different machine learning (ML) classifiers for discriminating low and high nuclear grade clear cell renal cell carcinomas (cc-RCCs).
Data Collection Kidney Neoplasms Carcinoma, Renal Cell Nephrectomy Tomography, X-Ray Computed Humans Machine Learning Female Male Algorithms Reproducibility of Results Middle Aged Retrospective Studies Aged Support Vector Machine Adult Diagnosis, Differential Bayes Theorem Biopsy
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