AIMC Topic: Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Machine Learning in Mass Spectrometry: A MALDI-TOF MS Approach to Phenotypic Antibacterial Screening.
Journal of medicinal chemistry
Apr 1, 2020
Machine learning techniques can be applied to MALDI-TOF mass spectral data of drug-treated cells to obtain classification models which assign the mechanism of action of drugs. Here, we present an example application of this concept to the screening o...
Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review.
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Mar 23, 2020
BACKGROUND: The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by facilitating precise and rapid species identification. Recently, machine learni...
Detection of carbapenem-resistant Klebsiella pneumoniae on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using supervised machine learning approach.
PloS one
Feb 6, 2020
BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a significant pathogen causing healthcare-associated infections. Matrix-assisted laser desorption/ionisation mass spectrometry time-of-flight mass spectrometry (MALDI-TOF MS...
Carbapenem-Resistant Enterobacteriaceae
Random Amplified Polymorphic DNA Technique
DNA, Bacterial
Klebsiella Infections
Predictive Value of Tests
Carbapenems
Cross Infection
Supervised Machine Learning
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Algorithms
Anti-Bacterial Agents
Microbial Sensitivity Tests
Klebsiella pneumoniae
Humans
Fast and Accurate Bacterial Species Identification in Urine Specimens Using LC-MS/MS Mass Spectrometry and Machine Learning.
Molecular & cellular proteomics : MCP
Oct 4, 2019
Fast identification of microbial species in clinical samples is essential to provide an appropriate antibiotherapy to the patient and reduce the prescription of broad-spectrum antimicrobials leading to antibioresistances. MALDI-TOF-MS technology has ...
Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter.
Scientific reports
Sep 13, 2019
Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immunoelectron microscopy and fluorescent fusion protein, have revealed great distribution diversity of m...
Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination.
Breast cancer research and treatment
Jul 8, 2019
PURPOSE: The aim of this study is to explore new salivary biomarkers to discriminate breast cancer patients from healthy controls.
Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma.
Scientific reports
May 28, 2019
Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a singl...
Female
Aged
Aged, 80 and over
Case-Control Studies
Metabolome
Male
Middle Aged
Humans
Neural Networks, Computer
Artificial Intelligence
Immunoglobulins
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Multiple Myeloma
Datasets as Topic
Principal Component Analysis
Metabolic Networks and Pathways
Bone Marrow
Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning.
Analytical chemistry
Apr 15, 2019
Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial information reflecting the molecular phenotypes and microenvironment of cells. To study the influence o...
MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods.
Proteomics. Clinical applications
Dec 14, 2018
PURPOSE: Precise histological classification of epithelial ovarian cancer (EOC) has immanent diagnostic and therapeutic consequences, but remains challenging in histological routine. The aim of this pilot study is to examine the potential of matrix-a...
Discrimination of contagious and environmental strains of Streptococcus uberis in dairy herds by means of mass spectrometry and machine-learning.
Scientific reports
Nov 30, 2018
Streptococcus uberis is one of the most common pathogens of clinical mastitis in the dairy industry. Knowledge of pathogen transmission route is essential for the selection of the most suitable intervention. Here we show that spectral profiles acquir...
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