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A support vector machine-based approach to guide the selection of a pseudo-reference region for brain PET quantification.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
A Support Vector Machine (SVM) based approach was developed to identify a pseudo-reference region for brain PET scans with the aim of reducing interscan and intersubject variability. By training a binary linear SVM classifier with PET datasets from t...

Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.

Biosensors & bioelectronics
The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...

A deep learning model for generating [F]FDG PET Images from early-phase [F]Florbetapir and [F]Flutemetamol PET images.

European journal of nuclear medicine and molecular imaging
INTRODUCTION: Amyloid-β (Aβ) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunct...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

Biomedical engineering online
BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta...

Increasing the confidence of F-Florbetaben PET interpretations: Machine learning quantitative approximation.

Revista espanola de medicina nuclear e imagen molecular
AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study the patterns of F-Florbetaben brain deposition.

Antifouling booster biocide extraction from marine sediments: a fast and simple method based on vortex-assisted matrix solid-phase extraction.

Environmental science and pollution research international
This paper reports the development of an analytical method employing vortex-assisted matrix solid-phase dispersion (MSPD) for the extraction of diuron, Irgarol 1051, TCMTB (2-thiocyanomethylthiobenzothiazole), DCOIT (4,5-dichloro-2-n-octyl-3-(2H)-iso...

Enhancing analysis throughput, sensitivity and specificity in LC/ESI-MS/MS assay of plasma 25-hydroxyvitamin D by derivatization with triplex 4-(4-dimethylaminophenyl)-1,2,4-triazoline-3,5-dione (DAPTAD) isotopologues.

Journal of pharmaceutical and biomedical analysis
The plasma/serum concentration of 25-hydroxyvitamin D [25(OH)D] is a diagnostic index for vitamin D deficiency/insufficiency, which is associated with a wide range of diseases, such as rickets, cancer and diabetes. We have reported that the derivatiz...

Generation of synthetic PET images of synaptic density and amyloid from F-FDG images using deep learning.

Medical physics
PURPOSE: Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isoto...

Modeling autosomal dominant Alzheimer's disease with machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.

Improved amyloid burden quantification with nonspecific estimates using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we p...