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Chemical Phenomena

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Physicochemical stability of etoposide diluted at range concentrations between 0.38 and 1.75 mg/mL in polyolefin bags.

European journal of hospital pharmacy : science and practice
INTRODUCTION: According to the manufacturers, the diluted solution of etoposide should not exceed 0.4 mg/mL because precipitation may occur. For high doses or for patients requiring fluid restrictions, etoposide phosphate may be an option but shortag...

Effects of different high hydrostatic pressure-treated potato starch on the processing performance of dough-like model systems.

Food research international (Ottawa, Ont.)
In this study, potato starch (PS) was processed by high hydrostatic pressure (HHP) at 200, 350 and 500 MPa for 30 min at 25 °C. Effects of HHP-treated PS on the processing performance of PS-gluten and PS-hydroxypropylmethylcellulose (HPMC) dough-like...

Sorptive equilibrium profile of fluoride onto aluminum olivine [(FeMg)SiO] composite (AOC): Physicochemical insights and isotherm modeling by non-linear least squares regression and a novel neural-network-based method.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
A novel aluminum/olivine composite (AOC) was prepared by wet impregnation followed by calcination and was introduced as an efficient adsorbent for defluoridation. The adsorption of fluoride was modeled with one-, two- and three-parameter isotherm equ...

A critical review on the use of artificial neural networks in olive oil production, characterization and authentication.

Critical reviews in food science and nutrition
Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neur...

Pectin extraction from Helianthus annuus (sunflower) heads using RSM and ANN modelling by a genetic algorithm approach.

International journal of biological macromolecules
In this work, Response Surface Methodology (RSM) and Artificial Neural Network coupled with genetic algorithm (ANN-GA) have been used to develop a model and optimise the conditions for the extraction of pectin from sunflower heads. Input parameters w...

Estimation of somatic cell count levels of hard cheeses using physicochemical composition and artificial neural networks.

Journal of dairy science
This study addresses the prediction of the somatic cell counts of the milk used in the production of sheep cheese using artificial neural networks. To achieve this objective, the neural network was designed using 33 parameters of the physicochemical ...

Identification of D Modification Sites by Integrating Heterogeneous Features in .

Molecules (Basel, Switzerland)
As an abundant post-transcriptional modification, dihydrouridine (D) has been found in transfer RNA (tRNA) from bacteria, eukaryotes, and archaea. Nonetheless, knowledge of the exact biochemical roles of dihydrouridine in mediating tRNA function is s...

mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides.

International journal of molecular sciences
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning ...

Deep Learning in Chemistry.

Journal of chemical information and modeling
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in t...

Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification.

Molecules (Basel, Switzerland)
Efficient identification of chemical probes for the manipulation and understanding of biological systems demands specificity for target proteins. Computational means to optimize candidate compound selection for experimental selectivity evaluation are...