AI Medical Compendium Topic:
COVID-19

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Optimizing Signal Management in a Vaccine Adverse Event Reporting System: A Proof-of-Concept with COVID-19 Vaccines Using Signs, Symptoms, and Natural Language Processing.

Drug safety
INTRODUCTION: The Vaccine Adverse Event Reporting System (VAERS) has already been challenged by an extreme increase in the number of individual case safety reports (ICSRs) after the market introduction of coronavirus disease 2019 (COVID-19) vaccines....

An adaptive ensemble deep learning framework for reliable detection of pandemic patients.

Computers in biology and medicine
Nurses, often considered the backbone of global health services, are disproportionately vulnerable to COVID-19 due to their front-line roles. They conduct essential patient tests, including blood pressure, temperature, and complete blood counts. The ...

Machine learning-driven development of a disease risk score for COVID-19 hospitalization and mortality: a Swedish and Norwegian register-based study.

Frontiers in public health
AIMS: To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway.

Deep learning hybrid model for analyzing and predicting the impact of imported malaria cases from Africa on the rise of Plasmodium falciparum in China before and during the COVID-19 pandemic.

PloS one
BACKGROUND: Plasmodium falciparum cases are rising in China due to the imported malaria cases from African countries. The main goal of this study is to examine the impact of imported malaria cases in African countries on the rise of P. falciparum cas...

Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review.

International journal of medical informatics
INTRODUCTION: Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of t...

Arts therapies for mental disorders in COVID-19 patients: a comprehensive review.

Frontiers in public health
BACKGROUND AND OBJECTIVE: The COVID-19 global pandemic has necessitated the urgency for innovative mental health interventions. We performed a comprehensive review of the available literature on the utility and efficacy of arts therapies in treating ...

Empowering COVID-19 detection: Optimizing performance through fine-tuned EfficientNet deep learning architecture.

Computers in biology and medicine
The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of individuals across the planet. It is a highly contagious respiratory disease requiring early and accurate detection to curb its rapid transmission. Initi...

Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning.

Biochemical genetics
The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coin...

A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Physical and engineering sciences in medicine
Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the d...

Humans are biocultural, science should be too.

Science (New York, N.Y.)
COVID-19 is restructuring societies. Loneliness is a global health threat. Large language models are outputting biased health care information, and human-artificial intelligence (AI) interfaces are reshaping how we live. For most humans, technology, ...