AIMC Topic: Complex Mixtures
Clear Filters Showing 1 to 10 of 10 articles
MS2Query: reliable and scalable MS mass spectra-based analogue search.
Nature communications
Mar 29, 2023
Metabolomics-driven discoveries of biological samples remain hampered by the grand challenge of metabolite annotation and identification. Only few metabolites have an annotated spectrum in spectral libraries; hence, searching only for exact library m...
Machine learning-assisted non-target analysis of a highly complex mixture of possible toxic unsymmetrical dimethylhydrazine transformation products with chromatography-mass spectrometry.
Chemosphere
Jul 18, 2022
Unsymmetrical dimethylhydrazine (UDMH) is a toxic and environmentally hostile compound that was massively introduced to the environment during previous decades due to its use in the space and rocket industry. The compound forms multiple transformatio...
Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition-Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils.
Molecules (Basel, Switzerland)
Oct 17, 2021
Scientific investigation on essential oils composition and the related biological profile are continuously growing. Nevertheless, only a few studies have been performed on the relationships between chemical composition and biological data. Herein, th...
Image learning to accurately identify complex mixture components.
The Analyst
Sep 27, 2021
The study of complex mixtures is very important for exploring the evolution of natural phenomena, but the complexity of the mixtures greatly increases the difficulty of material information extraction. Image perception-based machine-learning techniqu...
Identification of Specific Substances in the FAIMS Spectra of Complex Mixtures Using Deep Learning.
Sensors (Basel, Switzerland)
Sep 14, 2021
High-field asymmetric ion mobility spectrometry (FAIMS) spectra of single chemicals are easy to interpret but identifying specific chemicals within complex mixtures is difficult. This paper demonstrates that the FAIMS system can detect specific chemi...
Machine Vision Methods, Natural Language Processing, and Machine Learning Algorithms for Automated Dispersion Plot Analysis and Chemical Identification from Complex Mixtures.
Analytical chemistry
Jul 29, 2019
Gas-phase trace chemical detection techniques such as ion mobility spectrometry (IMS) and differential mobility spectrometry (DMS) can be used in many settings, such as evaluating the health condition of patients or detecting explosives at airports. ...
Application of the SeDeM Expert System in Studies for Direct Compression Suitability on Mixture of Rhodiola Extract and an Excipient.
AAPS PharmSciTech
Feb 11, 2019
The SeDeM expert system is used to reveal direct compression (DC) suitability of the active ingredients and excipients in preformulation. In this study, the system was used to predict compressibility of rhodiola extract (RhE) and its mixture with exc...
Prediction of bioavailability and toxicity of complex chemical mixtures through machine learning models.
Chemosphere
Oct 11, 2018
Empirical data from a 6-month mesocosms experiment were used to assess the ability and performance of two machine learning (ML) models, including artificial neural network (NN) and random forest (RF), to predict temporal bioavailability changes of co...
Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra.
Faraday discussions
Aug 15, 2019
Complex metabolite mixtures are challenging to unravel. Mass spectrometry (MS) is a widely used and sensitive technique for obtaining structural information of complex mixtures. However, just knowing the molecular masses of the mixture's constituents...
Extraction Optimization, Composition Analysis, and Antioxidation Evaluation of Polysaccharides from White Jelly Mushroom, Tremella fuciformis (Tremellomycetes).
International journal of medicinal mushrooms
Jan 1, 2017
We investigated the sonication-assisted extraction (SAE) conditions of Tremella fuciformis polysaccharides. Single-factor experiments showed that the optimal sonication intensity was 6 W/cm2; the other SAE conditions were further optimized using resp...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823