AIMC Topic: Aged, 80 and over

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Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease.

Scientific reports May 27, 2021
We report a new approach using artificial intelligence (AI) to study and classify the severity of COVID-19 using 1208 chest X-rays (CXRs) of 396 COVID-19 patients obtained through the course of the disease at Emory Healthcare affiliated hospitals (At...
Adolescent Image Processing, Computer-Assisted Area Under Curve Algorithms Radiography Male Humans Computer Simulation Middle Aged Female Neural Networks, Computer Disease Progression Aged Artificial Intelligence Severity of Illness Index Aged, 80 and over Deep Learning COVID-19 Adult
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Economic and utilization outcomes of medication management at a large Medicaid plan with disease management pharmacists using a novel artificial intelligence platform from 2018 to 2019: a retrospective observational study using regression methods.

Journal of managed care & specialty pharmacy May 25, 2021
Medication therapy management (MTM) and comprehensive medication management (CMM) have been practiced by clinical pharmacists as a predominantly manual activity with interventions documented in a record-keeping system. Program evaluations, largely b...
Adult Male Middle Aged Artificial Intelligence Infant Child Retrospective Studies Adolescent Humans United States Female Child, Preschool Regression Analysis Aged Medication Therapy Management Aged, 80 and over Medicaid Young Adult Pharmaceutical Services
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Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia May 24, 2021
Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aqueduct has been utilized for diagnosis of conditions such as normal pressure hydrocephalus (NPH). This...
Infant Deep Learning Adolescent Child, Preschool Humans Child Neural Networks, Computer Magnetic Resonance Imaging Young Adult Retrospective Studies Hydrocephalus, Normal Pressure Adult Female Cerebral Aqueduct Cross-Sectional Studies Infant, Newborn Male Aged Middle Aged Aged, 80 and over
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Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.

The American journal of pathology May 23, 2021
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA ...
Infant, Newborn Aged Aged, 80 and over Young Adult Adult Male Kidney Diseases Middle Aged Humans Biopsy Infant Female Deep Learning Fibrosis Adolescent Image Interpretation, Computer-Assisted Child, Preschool Child
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Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 21, 2021
BACKGROUND AND PURPOSE: Physical environmental factors are generally likely to become barriers for discharge to home of wheelchair users, compared with non-wheelchair users. However, the importance of environmental factors has not been investigated a...
Disability Evaluation Patient Discharge Stroke Activities of Daily Living Housing Female Aged Aged, 80 and over Male Treatment Outcome Environment Design Wheelchairs Self-Help Devices Humans Mobility Limitation Machine Learning Stroke Rehabilitation Decision Support Techniques Databases, Factual Clinical Decision-Making
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Integrative learning for population of dynamic networks with covariates.

NeuroImage May 20, 2021
Although there is a rapidly growing literature on dynamic connectivity methods, the primary focus has been on separate network estimation for each individual, which fails to leverage common patterns of information. We propose novel graph-theoretic ap...
Middle Aged Magnetic Resonance Imaging Unsupervised Machine Learning Connectome Nerve Net Computer Simulation Female Aged Aged, 80 and over Male Humans Neural Networks, Computer Brain
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Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Nature communications May 20, 2021
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...
Humans Adult Male Cardiovascular Diseases Middle Aged Risk Assessment Lung Retrospective Studies Tomography, X-Ray Computed Female Risk Factors Aged Aged, 80 and over Mass Screening Deep Learning Follow-Up Studies ROC Curve Datasets as Topic Image Processing, Computer-Assisted Coronary Vessels Lung Neoplasms Clinical Trials as Topic Electrocardiography
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COVID-19 and the kidney: A retrospective analysis of 37 critically ill patients using machine learning.

PloS one May 20, 2021
INTRODUCTION: There is evidence that SARS-CoV2 has a particular affinity for kidney tissue and is often associated with kidney failure.
Male Renal Replacement Therapy Humans Critical Illness Middle Aged Machine Learning Female Renal Insufficiency, Chronic COVID-19 Aged Body Mass Index Prognosis Aged, 80 and over Proteinuria Retrospective Studies Adult
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Application of deep learning to understand resilience to Alzheimer's disease pathology.

Brain pathology (Zurich, Switzerland) May 19, 2021
People who have Alzheimer's disease neuropathologic change (ADNC) typically associated with dementia but not the associated cognitive decline can be considered to be "resilient" to the effects of ADNC. We have previously reported lower neocortical le...
Algorithms Brain Female Aged Aged, 80 and over Alzheimer Disease Male tau Proteins Disease Progression Deep Learning Cognitive Dysfunction Humans Cognition Phosphorylation DNA-Binding Proteins
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Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT.

Scientific reports May 17, 2021
To develop an artificial intelligence (AI)-based method for the detection of focal skeleton/bone marrow uptake (BMU) in patients with Hodgkin's lymphoma (HL) undergoing staging with FDG-PET/CT. The results of the AI in a separate test group were comp...
Aged Aged, 80 and over Young Adult Adult Male Middle Aged Humans Biological Transport Neural Networks, Computer Radiopharmaceuticals Artificial Intelligence Fluorodeoxyglucose F18 Female Hodgkin Disease Adolescent Skeleton Child Musculoskeletal System Multimodal Imaging Positron Emission Tomography Computed Tomography Biopsy Bone Marrow
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