AIMC Topic:
SARS-CoV-2
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Repurposing therapeutics for COVID-19: Rapid prediction of commercially available drugs through machine learning and docking.
PloS one
Nov 12, 2020
BACKGROUND: The outbreak of the novel coronavirus disease COVID-19, caused by the SARS-CoV-2 virus has spread rapidly around the globe during the past 3 months. As the virus infected cases and mortality rate of this disease is increasing exponentiall...
Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency.
PloS one
Nov 12, 2020
AIMS: The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia.
Automatic detection of COVID-19 from chest radiographs using deep learning.
Radiography (London, England : 1995)
Nov 11, 2020
INTRODUCTION: The breakdown of a deadly infectious disease caused by a newly discovered coronavirus (named SARS n-CoV2) back in December 2019 has shown no respite to slow or stop in general. This contagious disease has spread across different lengths...
Cherry Tomato Production in Intelligent Greenhouses-Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality.
Sensors (Basel, Switzerland)
Nov 11, 2020
Greenhouses and indoor farming systems play an important role in providing fresh and nutritious food for the growing global population. Farms are becoming larger and greenhouse growers need to make complex decisions to maximize production and minimiz...
Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users' perceptions.
International journal of medical informatics
Nov 10, 2020
OBJECTIVE: The potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals' perceptions of the impact of weather can inform their adherence to public health gu...
The Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets.
Journal of medical Internet research
Nov 6, 2020
BACKGROUND: Family violence (including intimate partner violence/domestic violence, child abuse, and elder abuse) is a hidden pandemic happening alongside COVID-19. The rates of family violence are rising fast, and women and children are disproportio...
Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature.
Journal of medical Internet research
Nov 6, 2020
BACKGROUND: The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology ...
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, ...
Adult
Male
Middle Aged
Risk Assessment
Machine Learning
Hospitalization
Humans
ROC Curve
Pandemics
Acute Kidney Injury
Aged
Hospitals
Coronavirus Infections
COVID-19
Electronic Health Records
Aged, 80 and over
Adolescent
Prognosis
Female
Young Adult
Cohort Studies
SARS-CoV-2
Hospital Mortality
New York City
Betacoronavirus
Pneumonia, Viral
The COVID-19 pandemic: How predictive analysis, artificial intelligence and GIS can be integrated into a clinical command system to improve disaster response and preparedness.
The American journal of emergency medicine
Nov 2, 2020
Prototype Development of an Expert System of Computerized Clinical Guidelines for COVID-19 Diagnosis and Management in Saudi Arabia.
International journal of environmental research and public health
Nov 2, 2020
The increasing number of COVID-19 patients has increased health care professionals' workloads, making the management of dynamic patient information in a timely and comprehensive manner difficult and sometimes impossible. Compounding this problem is a...
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