AIMC Topic: COVID-19

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An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea.

Journal of global health
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
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
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)
: 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...

Deep neural networks excel in COVID-19 disease severity prediction-a meta-regression analysis.

Scientific reports
COVID-19 is a disease in which early prognosis of severity is critical for desired patient outcomes and for the management of limited resources like intensive care unit beds and ventilation equipment. Many prognostic statistical tools have been devel...

The role of generative artificial intelligence in psychiatric education- a scoping review.

BMC medical education
BACKGROUND: The growing prevalence of mental health conditions, worsened by the COVID-19 pandemic, highlights the urgent need for enhanced psychiatric education. The distinctive nature of psychiatry- which is heavily centred on communication skills, ...

Leveraging artificial intelligence to assess the impact of COVID-19 on the teacher-student relationship in higher education.

PloS one
The teacher-student relationship has far-reaching implications for educational outcomes at the tertiary level. Teachers contribute to students' success in various ways, including academic support, career counseling, personal mentoring, etc., that hel...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Journal of psychopathology and clinical science
Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use an...

Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism.

Scientific reports
The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious diseases is crucial for policymakers and healthcare systems. This study proposes a novel deep learning ap...

Performance evaluation of reduced complexity deep neural networks.

PloS one
Deep Neural Networks (DNN) have achieved state-of-the-art performance in medical image classification and are increasingly being used for disease diagnosis. However, these models are quite complex and that necessitates the need to reduce the model co...