AIMC Topic: Drug Resistance

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A simple scoring model based on machine learning predicts intravenous immunoglobulin resistance in Kawasaki disease.

Clinical rheumatology Jan 11, 2023
INTRODUCTION: In Kawasaki disease (KD), accurate prediction of intravenous immunoglobulin (IVIG) resistance is crucial to reduce a risk for developing coronary artery lesions.
ROC Curve Mucocutaneous Lymph Node Syndrome Immunoglobulins, Intravenous Drug Resistance Humans Machine Learning Retrospective Studies
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Graph Neural Network with Self-Supervised Learning for Noncoding RNA-Drug Resistance Association Prediction.

Journal of chemical information and modeling Jul 15, 2022
Noncoding RNA(ncRNA) is closely related to drug resistance. Identifying the association between ncRNA and drug resistance is of great significance for drug development. Methods based on biological experiments are often time-consuming and small-scale....
Supervised Machine Learning Drug Resistance RNA, Untranslated Neural Networks, Computer Computational Biology
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Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

PloS one May 18, 2022
In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computational methods have been developed for drug sensitivity prediction and the identification of related...
Gene Regulatory Networks ErbB Receptors Neural Networks, Computer Drug Resistance Machine Learning
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A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.

PloS one Aug 27, 2020
Kawasaki disease is the leading cause of pediatric acquired heart disease. Coronary artery abnormalities are the main complication of Kawasaki disease. Kawasaki disease patients with intravenous immunoglobulin resistance are at a greater risk of deve...
Humans Machine Learning Male Risk Assessment Infant China Retrospective Studies Female Risk Factors Models, Biological Immunoglobulins, Intravenous Drug Resistance Mucocutaneous Lymph Node Syndrome Child, Preschool Coronary Artery Disease ROC Curve Feasibility Studies Logistic Models
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An improved fuzzy set-based multifactor dimensionality reduction for detecting epistasis.

Artificial intelligence in medicine Nov 22, 2019
OBJECTIVE: Epistasis identification is critical for determining susceptibility to human genetic diseases. The rapid development of technology has enabled scalability to make multifactor dimensionality reduction (MDR) measurements an effective calcula...
Drug Resistance, Multiple Drug Resistance Epistasis, Genetic Multifactor Dimensionality Reduction Genotype Artificial Intelligence Humans Models, Genetic Fuzzy Logic Algorithms Case-Control Studies
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ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder.

Genes Nov 7, 2019
Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to take effect. This limitation may result in increased risks and treatment costs. To address this limitat...
Drug Resistance Depressive Disorder, Major Treatment Outcome Antidepressive Agents Neural Networks, Computer Software Humans
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Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction.

PloS one Oct 7, 2019
The prediction of cell-lines sensitivity to a given set of compounds is a very important factor in the optimization of in-vitro assays. To date, the most common prediction strategies are based upon machine learning or other quantitative structure-act...
Quantitative Structure-Activity Relationship Animals Drug Discovery Drug Resistance Humans Cell Line Small Molecule Libraries Machine Learning Software
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Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.

Analytica chimica acta Sep 25, 2019
Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absen...
Mass Spectrometry Metabolomics Humans HCT116 Cells Antineoplastic Agents Irinotecan Proof of Concept Study Neural Networks, Computer ROC Curve Drug Resistance Machine Learning Single-Cell Analysis Biomarkers
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Can Machine Learning help us in dealing with treatment resistant depression? A review.

Journal of affective disorders Aug 13, 2019
BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms relief and up to 15% of patients remain symptomatic even after multiple trials are applied, configuring a state called treatment resistant depression ...
Algorithms Male Depressive Disorder, Treatment-Resistant Female Disease Management Drug Resistance Humans Adult Antidepressive Agents Evidence-Based Practice Machine Learning
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A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Journal of biophotonics May 30, 2019
Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, au...
Eimeria Dogs Goats Microscopy Feces Animals Image Processing, Computer-Assisted Neural Networks, Computer Deep Learning Robotics Sheep Specimen Handling Machine Learning Drug Resistance Pattern Recognition, Automated Haplorhini Parasitemia Anthelmintics
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