AIMC Topic: Aged, 80 and over

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A Prospective Validation and Observer Performance Study of a Deep Learning Algorithm for Pathologic Diagnosis of Gastric Tumors in Endoscopic Biopsies.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 10, 2020
PURPOSE: Gastric cancer remains the leading cause of cancer-related deaths in Northeast Asia. Population-based endoscopic screenings in the region have yielded successful results in early detection of gastric tumors. Endoscopic screening rates are co...
Gastroscopy Gastric Mucosa Humans Prospective Studies Retrospective Studies Female Aged Aged, 80 and over Deep Learning Biopsy Adult Feasibility Studies Stomach Neoplasms Pathologists Sensitivity and Specificity Image Interpretation, Computer-Assisted Male Observer Variation Middle Aged
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Humans Predictive Value of Tests Neural Networks, Computer Phenotype Middle Aged Female Signal Processing, Computer-Assisted Prospective Studies Risk Assessment Risk Factors Ventricular Fibrillation Myocardial Infarction Prognosis Diagnosis, Computer-Assisted Aged Tachycardia, Ventricular Death, Sudden, Cardiac Time Factors Cardiomyopathies Aged, 80 and over Electrophysiologic Techniques, Cardiac Support Vector Machine Male Action Potentials
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Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology Nov 10, 2020
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...
Male Middle Aged Risk Assessment Adolescent Female Anemia, Sickle Cell Humans Hospitalization Machine Learning Aged Algorithms Aged, 80 and over Patient Readmission Young Adult Adult
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Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates.

Biomolecules Nov 10, 2020
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 im...
ROC Curve Predictive Value of Tests Aged Radiography Humans Hip Aged, 80 and over Neural Networks, Computer Male Bone Density Middle Aged Osteoporosis Deep Learning Female
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Major colorectal resection is feasible using a new robotic surgical platform: the first report of a case series.

Techniques in coloproctology Nov 6, 2020
BACKGROUND: The number of abdominal procedures performed via a robotic-assisted approach is increasing as potential advantages of the modality are recognised. We report the first in human case series of major colorectal resection performed using a ne...
Rectum Middle Aged Treatment Outcome Robotics Laparoscopy Robotic Surgical Procedures Aged, 80 and over Young Adult Adult Humans Colorectal Neoplasms Female Male Aged
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Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

Journal of medical Internet research Nov 6, 2020
BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, ...
Hospitalization Aged Aged, 80 and over Young Adult Adult Male Prognosis Acute Kidney Injury Electronic Health Records Female SARS-CoV-2 Hospital Mortality ROC Curve Coronavirus Infections New York City Betacoronavirus Middle Aged Pneumonia, Viral Risk Assessment Hospitals Humans Adolescent Cohort Studies Machine Learning Pandemics COVID-19
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Development and Validation of a Deep Learning-Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images.

AJNR. American journal of neuroradiology Nov 5, 2020
BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learni...
Magnetic Resonance Imaging Alzheimer Disease Image Interpretation, Computer-Assisted Neuroimaging Humans Algorithms Female Aged Aged, 80 and over Male Middle Aged Deep Learning Cognitive Dysfunction Imaging, Three-Dimensional
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Host variables confound gut microbiota studies of human disease.

Nature Nov 4, 2020
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false...
Machine Learning Data Analysis Female Aged Aged, 80 and over Young Adult Humans Residence Characteristics Area Under Curve Gastrointestinal Motility Alcohol Drinking Disease Life Style Confounding Factors, Epidemiologic Feces ROC Curve Adult Diabetes Mellitus, Type 2 Male Body Mass Index Middle Aged Gastrointestinal Microbiome Diet RNA, Ribosomal, 16S Case-Control Studies
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Left ventricular systolic dysfunction identification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

International journal of cardiology Nov 2, 2020
BACKGROUND: An artificial intelligence-augmented electrocardiogram (AI-ECG) can identify left ventricular systolic dysfunction (LVSD). We examined the accuracy of AI ECG for identification of LVSD (defined as LVEF ≤40% by transthoracic echocardiogram...
Artificial Intelligence Intensive Care Units Female Aged Aged, 80 and over Male Humans Echocardiography Middle Aged Electrocardiography Ventricular Dysfunction, Left
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Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies.

JAMA network open Nov 2, 2020
IMPORTANCE: Expert-level artificial intelligence (AI) algorithms for prostate biopsy grading have recently been developed. However, the potential impact of integrating such algorithms into pathologist workflows remains largely unexplored.
Middle Aged Prostatic Neoplasms Neoplasm Grading Biopsy, Large-Core Needle Humans Pathology, Clinical Artificial Intelligence Retrospective Studies Aged Aged, 80 and over Adult Male
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