AIMC Topic: Aged, 80 and over

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Prognostic networks for unraveling the biological mechanisms of Sarcopenia.

Mechanisms of ageing and development Aug 21, 2019
Sarcopenia is an age-related multifactorial process that involved several biological mechanisms, whose specific contribution and interplay is still unknown. The present study proposes prognostic networks based on machine learning approaches to unrave...
Aged, 80 and over Male Sarcopenia Humans Machine Learning Prognosis Female Aged
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Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.

IEEE transactions on medical imaging Aug 20, 2019
ABUS, or Automated breast ultrasound, is an innovative and promising method of screening for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains operator-independent image acquisition and also provides 3D views of the whole bre...
Breast Neoplasms Middle Aged Deep Learning Ultrasonography, Mammary Breast Supervised Machine Learning Image Interpretation, Computer-Assisted Female Aged Aged, 80 and over Adult Sensitivity and Specificity Humans
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Machine Learning Diagnosis of Peritonsillar Abscess.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Aug 20, 2019
Peritonsillar abscess (PTA) is a difficult diagnosis to make clinically, with clinical examination of even otolaryngologists showing poor sensitivity and specificity. Machine learning is a form of artificial intelligence that "learns" from data to ma...
Humans Machine Learning Middle Aged Infant Adolescent Child, Preschool Child Aged, 80 and over Algorithms Logistic Models Young Adult Retrospective Studies Symptom Assessment Adult Female Peritonsillar Abscess Aged Sensitivity and Specificity Male
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Performance of an artificial intelligence algorithm for reporting urine cytopathology.

Cancer cytopathology Aug 14, 2019
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with ur...
Deep Learning Urinary Bladder Neoplasms Feasibility Studies Image Interpretation, Computer-Assisted Observer Variation Aged Aged, 80 and over Sensitivity and Specificity Middle Aged Humans Female Carcinoma, Transitional Cell Urine Urothelium
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Predicting Clinical Outcomes of Large Vessel Occlusion Before Mechanical Thrombectomy Using Machine Learning.

Stroke Aug 14, 2019
Background and Purpose- The clinical course of acute ischemic stroke with large vessel occlusion (LVO) is a multifactorial process with various prognostic factors. We aimed to model this process with machine learning and predict the long-term clinica...
Predictive Value of Tests Cerebrovascular Disorders Thrombectomy Male Middle Aged Cohort Studies Treatment Outcome Humans Machine Learning Retrospective Studies Female Aged Aged, 80 and over
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Effects of a robot intervention on visuospatial hemineglect in postacute stroke patients: a randomized controlled trial.

Clinical rehabilitation Aug 13, 2019
OBJECTIVE: To evaluate the effects of an intervention using the robot device PARO on visuospatial hemineglect and activities of daily living, and its acceptance during stroke rehabilitation. PARO is an interactive robotic toy with the appearance of a...
Humans Female Recovery of Function Robotics Stroke Activities of Daily Living Stroke Rehabilitation Aged Aged, 80 and over Male Middle Aged Treatment Outcome Spatial Navigation Agnosia
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Home care aides' observations and machine learning algorithms for the prediction of visits to emergency departments by older community-dwelling individuals receiving home care assistance: A proof of concept study.

PloS one Aug 13, 2019
BACKGROUND: Older individuals receiving home assistance are at high risk for emergency visits and unplanned hospitalization. Anticipating their health difficulties could prevent these events. This study investigated the effectiveness of an at-home mo...
Surveys and Questionnaires Female Humans Geriatric Assessment Frail Elderly Proof of Concept Study Hospitalization Machine Learning Predictive Value of Tests Independent Living Aged Algorithms Emergency Service, Hospital Home Care Services Prospective Studies Aged, 80 and over Home Health Aides Male
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Neural-network classification of cardiac disease from P cardiovascular magnetic resonance spectroscopy measures of creatine kinase energy metabolism.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Aug 12, 2019
BACKGROUND: The heart's energy demand per gram of tissue is the body's highest and creatine kinase (CK) metabolism, its primary energy reserve, is compromised in common heart diseases. Here, neural-network analysis is used to test whether noninvasive...
Magnetic Resonance Spectroscopy Phosphocreatine Phosphorus Isotopes Kinetics Adenosine Triphosphate Heart Diseases Energy Metabolism Aged, 80 and over Young Adult Adult Male Middle Aged Machine Learning Severity of Illness Index Biomarkers Predictive Value of Tests Female Humans Myocardium Reproducibility of Results Creatine Kinase Neural Networks, Computer Aged
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An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 11, 2019
Cancer has been one of the most threatening diseases to human health. There have been many efforts devoted to the advancement of radiology and transformative tools (e.g. non-invasive computed tomographic or CT imaging) to detect cancer in early stage...
Aged Diagnosis, Computer-Assisted Humans Aged, 80 and over Lung Neoplasms Neural Networks, Computer Colorectal Neoplasms Tomography, X-Ray Computed Diagnosis, Differential Male Female Datasets as Topic Middle Aged
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Knowledge-based and deep learning-based automated chest wall segmentation in magnetic resonance images of extremely dense breasts.

Medical physics Aug 10, 2019
PURPOSE: Segmentation of the chest wall, is an important component of methods for automated analysis of breast magnetic resonance imaging (MRI). Methods reported to date show promising results but have difficulties delineating the muscle border corre...
Humans Female Magnetic Resonance Imaging Breast Automation Thoracic Wall Breast Density Aged Aged, 80 and over Middle Aged Deep Learning Image Processing, Computer-Assisted
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