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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.
Neuroimaging clinics of North America
Sep 17, 2020
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolut...
Primary Prevention Trial Designs Using Coronary Imaging: A National Heart, Lung, and Blood Institute Workshop.
JACC. Cardiovascular imaging
Sep 16, 2020
Coronary artery calcium (CAC) is considered a useful test for enhancing risk assessment in the primary prevention setting. Clinical trials are under consideration. The National Heart, Lung, and Blood Institute convened a multidisciplinary working gro...
Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.
Radiologic clinics of North America
Sep 14, 2020
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...
Practice Guidelines as Topic
Immunohistochemistry
Ultrasonography, Doppler
Biopsy, Needle
Incidental Findings
Magnetic Resonance Imaging
Diagnostic Imaging
Positron Emission Tomography Computed Tomography
Radiologists
Thyroid Neoplasms
Thyroid Nodule
United States
Humans
Artificial Intelligence
Clinical Decision-Making
Female
Male
Incidence
Artificial intelligence in trauma systems.
Surgery
Sep 10, 2020
Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data analysis mechanisms to improve timely access to care, to measure outcomes, and to improve quality of...
British Sign Language Recognition via Late Fusion of Computer Vision and Leap Motion with Transfer Learning to American Sign Language.
Sensors (Basel, Switzerland)
Sep 9, 2020
In this work, we show that a late fusion approach to multimodality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of image classification (88.14%) and Leap Motion data classification (7...
Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.
JAMA network open
Sep 1, 2020
IMPORTANCE: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention.
Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.
Journal of the American Medical Directors Association
Aug 27, 2020
OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach.
Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques.
Journal of medical Internet research
Aug 21, 2020
BACKGROUND: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which...
Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S.
International journal of environmental research and public health
Aug 20, 2020
The current study examined the predictive ability of discrimination-related variables, coping mechanisms, and sociodemographic factors on the psychological distress level of Korean immigrants in the U.S. amid the COVID-19 pandemic. Korean immigrants ...
Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence.
Journal of medical Internet research
Aug 18, 2020
BACKGROUND: The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic.
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