AIMC Topic: COVID-19
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Machine learning approaches for real-time ZIP code and county-level estimation of state-wide infectious disease hospitalizations using local health system data.
Epidemics
Apr 3, 2025
The lack of conventional methods of estimating real-time infectious disease burden in granular regions inhibits timely and efficient public health response. Comprehensive data sources (e.g., state health department data) typically needed for such est...
Using artificial intelligence tools to automate data extraction for living evidence syntheses.
PloS one
Apr 3, 2025
Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article sea...
Machine learning in point-of-care testing: innovations, challenges, and opportunities.
Nature communications
Apr 2, 2025
The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (...
Machine learning algorithms applied to the diagnosis of COVID-19 based on epidemiological, clinical, and laboratory data.
Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia
Mar 31, 2025
OBJECTIVE: To predict COVID-19 in hospitalized patients with SARS in a city in southern Brazil by using machine learning algorithms.
Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.
Molecular diversity
Mar 28, 2025
Antiviral peptides (AVPs) represent a novel and promising therapeutic alternative to conventional antiviral treatments, due to their broad-spectrum activity, high specificity, and low toxicity. The emergence of zoonotic viruses such as Zika, Ebola, a...
Clinicians' Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study.
Journal of medical Internet research
Mar 28, 2025
BACKGROUND: Interest in integrating robotics within intensive care units (ICUs) has been propelled by technological advancements, workforce challenges, and heightened clinical demands, including during the COVID-19 pandemic. The integration of roboti...
An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea.
Journal of global health
Mar 28, 2025
BACKGROUND: Modelling can contribute to disease prevention and control strategies. Accurate predictions of future cases and mortality rates were essential for establishing appropriate policies during the COVID-19 pandemic. However, no single model yi...
Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post-COVID-19 Condition: Protocol for an Observational Study.
JMIR research protocols
Mar 27, 2025
BACKGROUND: Post-COVID-19 condition is emerging as a new epidemic, characterized by the persistence of COVID-19 symptoms beyond 3 months, and is anticipated to substantially alter the lives of millions of people globally. Patients with severe episode...
[Therapeutic patient education and telemedicine in the age of artificial intelligence].
Revue de l'infirmiere
Mar 27, 2025
Since the promulgation of the July 21, 2009 law on hospital reform and patients, health and territories, known as the HPST law, therapeutic patient education (TPE) and telemedicine have become key pillars in the modernization of the healthcare system...
Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.
Medicina (Kaunas, Lithuania)
Mar 26, 2025
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...
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