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SARS-CoV-2
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SMMPPI: a machine learning-based approach for prediction of modulators of protein-protein interactions and its application for identification of novel inhibitors for RBD:hACE2 interactions in SARS-CoV-2.
Briefings in bioinformatics
Sep 2, 2021
Small molecule modulators of protein-protein interactions (PPIs) are being pursued as novel anticancer, antiviral and antimicrobial drug candidates. We have utilized a large data set of experimentally validated PPI modulators and developed machine le...
Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.
The Journal of the Acoustical Society of America
Sep 1, 2021
This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters were extracted from voice samples of 203 COVID-19 patients and 17...
Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID-19.
Clinical and translational medicine
Sep 1, 2021
Evaluation of the prediction of CoVID-19 recovered and unrecovered cases using symptoms and patient's meta data based on support vector machine, neural network, CHAID and QUEST Models.
European review for medical and pharmacological sciences
Sep 1, 2021
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...
Adoption of Digital Pathology in Developing Countries: From Benefits to Challenges.
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
Sep 1, 2021
Digital pathology and the use of artificial intelligence constitute undisputedly the future of modern pathology. The outcomes and benefits of the whole slide imaging are beyond the scope of traditional microscopy, which the pathologists were using fo...
Auto informing COVID-19 detection result from x-ray/CT images based on deep learning.
The Review of scientific instruments
Aug 1, 2021
It is no secret to all that the corona pandemic has caused a decline in all aspects of the world. Therefore, offering an accurate automatic diagnostic system is very important. This paper proposed an accurate COVID-19 system by testing various deep l...
An artificial neural network model to predict the mortality of COVID-19 patients using routine blood samples at the time of hospital admission: Development and validation study.
Medicine
Jul 16, 2021
BACKGROUND:: In a pandemic situation (e.g., COVID-19), the most important issue is to select patients at risk of high mortality at an early stage and to provide appropriate treatments. However, a few studies applied the model to predict in-hospital m...
Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129.
Cardiovascular research
Jul 7, 2021
The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO)...
Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.
Nucleic acids research
Jul 2, 2021
Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-bas...
ModFOLD8: accurate global and local quality estimates for 3D protein models.
Nucleic acids research
Jul 2, 2021
Methods for estimating the quality of 3D models of proteins are vital tools for driving the acceptance and utility of predicted tertiary structures by the wider bioscience community. Here we describe the significant major updates to ModFOLD, which ha...
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