AI Medical Compendium Topic

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SARS-CoV-2

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Cooperating Graph Neural Networks With Deep Reinforcement Learning for Vaccine Prioritization.

IEEE journal of biomedical and health informatics
This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing vaccine distribution methods focus on macro-level or simplified micro-level assuming homogeneous behavior within...

Navigating artificial intelligence in care homes: Competing stakeholder views of trust and logics of care.

Social science & medicine (1982)
The COVID-19 pandemic shed light on systemic issues plaguing care (nursing) homes, from staff shortages to substandard healthcare. Artificial Intelligence (AI) technologies, including robots and chatbots, have been proposed as solutions to such issue...

Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

Vaccine
BACKGROUND: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of what causes delay/refusal of SARS-CoV-2 vaccination and limited ability to predict who will remain unvaccinated over significant time periods despite v...

From Policy to Prediction: Assessing Forecasting Accuracy in an Integrated Framework with Machine Learning and Disease Models.

Journal of computational biology : a journal of computational molecular cell biology
To improve the forecasting accuracy of the spread of infectious diseases, a hybrid model was recently introduced where the commonly assumed constant disease transmission rate was actively estimated from enforced mitigating policy data by a machine le...

An architecture for COVID-19 analysis and detection using big data, AI, and data architectures.

PloS one
The COVID-19 epidemic is affecting individuals in many ways and continues to spread all over the world. Vaccines and traditional medical techniques are still being researched. In diagnosis and therapy, biological and digital technology is used to ove...

Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.

Talanta
This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients...

The Lag -Effects of Air Pollutants and Meteorological Factors on COVID-19 Infection Transmission and Severity: Using Machine Learning Techniques.

Journal of research in health sciences
BACKGROUND: Exposure to air pollution is a major health problem worldwide. This study aimed to investigate the effect of the level of air pollutants and meteorological parameters with their related lag time on the transmission and severity of coronav...

Performance of artificial intelligence in predicting the prognossis of severe COVID-19: a systematic review and meta-analysis.

Frontiers in public health
BACKGROUND: COVID-19-induced pneumonia has become a persistent health concern, with severe cases posing a significant threat to patient lives. However, the potential of artificial intelligence (AI) in assisting physicians in predicting the prognosis ...

A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods.

SAR and QSAR in environmental research
The 3C-like Proteinase (3CLpro) of novel coronaviruses is intricately linked to viral replication, making it a crucial target for antiviral agents. In this study, we employed two fingerprint descriptors (ECFP_4 and MACCS) to comprehensively character...

Shape prior-constrained deep learning network for medical image segmentation.

Computers in biology and medicine
We propose a shape prior representation-constrained multi-scale features fusion segmentation network for medical image segmentation, including training and testing stages. The novelty of our training framework lies in two modules comprised of the sha...