A5037005564- COVID-19 Clinical Research Studies
- COVID-19 diagnosis using AI
- SARS-CoV-2 and COVID-19 Research
- Protein Structure and Dynamics
- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Long-Term Effects of COVID-19
- Respiratory Support and Mechanisms
- Artificial Intelligence in Healthcare
Weatherford College
2021
Abstract COVID-19 is a newly emerging infectious disease, which generally susceptible to human beings and has caused huge losses people's health. Acute respiratory distress syndrome (ARDS) one of the common clinical manifestations severe it also responsible for current shortage ventilators worldwide. This study aims analyze characteristics ARDS patients establish diagnostic system based on artificial intelligence (AI) method predict probability in patients. We collected data 659 from 11...
Abstract With the dramatically fast spread of COVID-9, real-time reverse transcription polymerase chain reaction (RT-PCR) test has become gold standard method for confirmation COVID-19 infection. However, RT-PCR tests are complicated in operation andIt usually takes 5-6 hours or even longer to get result. Additionally, due low virus loads early patients, display false negative results a number cases. Analyzing complex medical datasets based on machine learning provides health care workers...
Early determination of coronavirus disease 2019 (COVID-19) pneumonia from numerous suspected cases is critical for the early isolation and treatment patients.The purpose study was to develop validate a rapid screening model predict COVID-19 using random forest algorithm in China.A total 914 initially multiple centers were prospectively included. The computer-assisted embedding method used screen variables. adopted build based on training set. evaluated by confusion matrix receiver operating...
One of the crucial objectives in modern drug design is generation high-quality novel molecules. Currently, numerous deep learning methods have been applied field molecular generation. Modeling molecules as graph-structured data provides a unique representation that offers richer structural information than sequential data. However, unlike such images, conventional embedding struggle to capture topological structure graphs and distinguish between different types nodes edges, leading loss...
Abstract Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this from huge numbers suspects gives clinicians a big challenge. The aim the study was to develop rapid screening model for early predicting NCP Zhejiang population, as well its utility areas. A total 880 participants who were initially suspected January 17 February 19 included. Potential predictors selected via stepwise logistic regression analysis. established based on...