AIMC Topic: United States

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Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction.

JACC. Heart failure Oct 9, 2019
OBJECTIVES: This study sought to develop models for predicting mortality and heart failure (HF) hospitalization for outpatients with HF with preserved ejection fraction (HFpEF) in the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with...
Humans Machine Learning Prognosis Female Heart Failure Brazil Risk Factors Argentina Male ROC Curve Hospitalization Stroke Volume Canada Aged Middle Aged Health Status United States Survival Rate Risk Assessment Double-Blind Method
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Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Oct 1, 2019
This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of M...
Europe Radiology Radiologists Societies, Medical Artificial Intelligence Consensus Canada United States Humans
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Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement.

Radiology Oct 1, 2019
This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of M...
United States Europe Radiology Radiologists Societies, Medical Humans Artificial Intelligence Consensus Canada
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The role of AI in diagnosing lung diseases.

The Lancet. Respiratory medicine Sep 26, 2019
Role United States Humans Lung Diseases Artificial Intelligence United States Food and Drug Administration Female Information Dissemination Male
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A comparison of machine learning algorithms for the surveillance of autism spectrum disorder.

PloS one Sep 25, 2019
OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speedi...
Child Humans United States Autism Spectrum Disorder Feasibility Studies Prevalence Support Vector Machine Epidemiological Monitoring Deep Learning Public Health Surveillance Georgia Centers for Disease Control and Prevention, U.S.
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Comparing artificial intelligence techniques for chlorophyll-a prediction in US lakes.

Environmental science and pollution research international Sep 3, 2019
Chlorophyll-a (CHLA) is a key indicator to represent eutrophication status in lakes. In this study, CHLA, total phosphorus (TP), total nitrogen (TN), turbidity (TB), and Secchi depth (SD) collected by the United States Environmental Protection Agency...
United States Environmental Monitoring Cluster Analysis Nitrogen Algorithms Ecosystem Eutrophication Lakes United States Environmental Protection Agency Phosphorus Water Quality Chlorophyll Chlorophyll A Artificial Intelligence
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Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.

The Lancet. Digital health Aug 27, 2019
BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approac...
Humans Machine Learning Biomarkers Parkinson Disease Austria Germany Parkinsonian Disorders Multiple System Atrophy Male Supranuclear Palsy, Progressive Brain Anisotropy Middle Aged Female Cohort Studies Diffusion Magnetic Resonance Imaging Reproducibility of Results United States Aged
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Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.

The Lancet. Digital health Aug 27, 2019
BACKGROUND: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.
United States Humans Austria Germany Machine Learning Parkinsonian Disorders Image Processing, Computer-Assisted
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Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.

The Journal of investigative dermatology Aug 22, 2019
Child, Preschool Child United States Longitudinal Studies Age of Onset Dermatitis, Atopic Cluster Analysis Registries Male Infant Severity of Illness Index Diagnosis, Computer-Assisted Machine Learning Phenotype Humans Female Infant, Newborn
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Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data.

PloS one Aug 22, 2019
Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Force (USPSTF) recommends anyone ages 50-75 and/or with a family history to be screened for CRC. To impr...
Health Status Early Detection of Cancer Models, Statistical Self Report Practice Guidelines as Topic Humans Medical History Taking Middle Aged Neural Networks, Computer Aged Health Surveys Colorectal Neoplasms Prognosis United States Male Female Diabetes Mellitus Cardiovascular Diseases Risk Factors
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