AIMC Topic: COVID-19 Drug Treatment
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A versatile attention-based neural network for chemical perturbation analysis and its potential to aid surgical treatment: an experimental study.
International journal of surgery (London, England)
Dec 1, 2024
Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decisions. Through a combination of drug screening and deep learning models, drugs that may benefit patients before and after surgery can be discovered to red...
A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.
NPJ systems biology and applications
Nov 27, 2024
Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses like SARS-CoV-2. Yet, conventional assays are labor intensive and cannot capture the full spectrum of...
A deep drug prediction framework for viral infectious diseases using an optimizer-based ensemble of convolutional neural network: COVID-19 as a case study.
Molecular diversity
Oct 9, 2024
The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emerging microbial threats, emphasizing the lack of time to develop disease-specific treatments. Therefore, it appears beneficial to utilize existing resourc...
Large-scale deep learning identifies the antiviral potential of PKI-179 and MTI-31 against coronaviruses.
Antiviral research
Sep 25, 2024
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the global pandemic of Coronavirus Disease (2019) (COVID-19), underscoring the urgency for effective antiviral drugs. Despite the development of different vaccination strategies,...
A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.
JAMA health forum
Sep 6, 2024
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...
Aged
Young Adult
Adult
Male
Female
SARS-CoV-2
Hospitalization
Health Policy
Antibodies, Monoclonal
Random Forest
United States Food and Drug Administration
Middle Aged
Severity of Illness Index
Adolescent
Antibodies, Viral
Humans
Machine Learning
COVID-19
Retrospective Studies
Electronic Health Records
COVID-19 Drug Treatment
Health Care Rationing
Emergency Use Authorization
Construction of a multi-tissue compound-target interaction network of Qingfei Paidu decoction in COVID-19 treatment based on deep learning and transcriptomic analysis.
Journal of bioinformatics and computational biology
Jul 20, 2024
The Qingfei Paidu decoction (QFPDD) is a widely acclaimed therapeutic formula employed nationwide for the clinical management of coronavirus disease 2019 (COVID-19). QFPDD exerts a synergistic therapeutic effect, characterized by its multi-component,...
Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.
Inflammopharmacology
May 19, 2024
BACKGROUND: Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study...
Accelerating reliable multiscale quantum refinement of protein-drug systems enabled by machine learning.
Nature communications
May 16, 2024
Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechanics (QM) methods in crystallographic refinement, showed promise in improving the structural quality ...
A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs.
PeerJ
May 13, 2024
INTRODUCTION: This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension who were treated with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor B (ARB) drugs and to identify key features affecting patient...
Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.
PloS one
May 10, 2024
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as ...
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