AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Drug Evaluation, Preclinical

Showing 151 to 160 of 182 articles

Clear Filters

Cytotoxicity of chitosan/streptokinase nanoparticles as a function of size: An artificial neural networks study.

Nanomedicine : nanotechnology, biology, and medicine
Predicting the size and toxicity of chitosan/streptokinase nanoparticles at various values of processing parameters was the aim of this study. For the first time, a comprehensive model could be developed to determine the cytotoxicity of the nanoparti...

Comparative evaluation of different cultivars of Flos Chrysanthemi by an anti-inflammatory-based NF-κB reporter gene assay coupled to UPLC-Q/TOF MS with PCA and ANN.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Flos Chrysanthemi (FC), a commonly used traditional Chinese medicine, has five major cultivars ("Boju", "Chuju", "Gongju", "Hangbaiju" and "Huaiju") from different sources. However, the active constituents of these cul...

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

Drug development and industrial pharmacy
As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necess...

Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

European journal of medicinal chemistry
The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protea...

Visualization and Interpretation of Support Vector Machine Activity Predictions.

Journal of chemical information and modeling
Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other...

Experimental design strategy: weak reinforcement leads to increased hit rates and enhanced chemical diversity.

Journal of chemical information and modeling
High Throughput Screening (HTS) is a common approach in life sciences to discover chemical matter that modulates a biological target or phenotype. However, low assay throughput, reagents cost, or a flowchart that can deal with only a limited number o...

Systematic artifacts in support vector regression-based compound potency prediction revealed by statistical and activity landscape analysis.

PloS one
Support vector machines are a popular machine learning method for many classification tasks in biology and chemistry. In addition, the support vector regression (SVR) variant is widely used for numerical property predictions. In chemoinformatics and ...

Increase Docking Score Screening Power by Simple Fusion With CNNscore.

Journal of computational chemistry
Scoring functions (SFs) of molecular docking is a vital component of structure-based virtual screening (SBVS). Traditional SFs yield their inherent shortage for idealized approximations and simplifications predicting the binding affinity. Complementa...

COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.

Journal of computational chemistry
Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachidonic acid into prostaglandins. The overexpression of enzyme is associated with conditions such as cancer, arthritis, and Alzheimer's disease (AD), wh...

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

Protein science : a publication of the Protein Society
The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a...