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Discriminant Analysis

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Compositional analysis of alternative protein blends using near and mid-infrared spectroscopy coupled with conventional and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive real-time analysis of the composition of alternative, plant-based protein sources is important to control high moisture extrusion processes and ensure the quality and texture of the final extrudates used in the elaboration of meat an...

Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.

Analytical chemistry
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluids for molecular profiling. Nevertheless, the current methods often lack the sensitivity and specificity necessary for early detection and real-time mo...

Rapid identification of coffee species and origin using affordable multi-channel spectral sensor combined with machine learning.

Food research international (Ottawa, Ont.)
The rapid identification of coffee species and origin is critical for ensuring quality control and authenticity in the coffee industry. This study explores the use of an affordable multi-channel spectral sensor, AS7265X (410-940 nm), combined with ma...

A comparative study of neural network architectures for vital signs monitoring based on the national early warning systems (NEWS).

Health informatics journal
The study aims to assess the efficacy of various neural network architectures in predicting the National Early Warning Systems (NEWS) score, using vital signs, to enhance early warning and monitoring in clinical settings. A comparative evaluation o...

Getting Started with Machine Learning for Experimental Biochemists and Other Molecular Scientists.

Current protocols
Machine learning (ML) is rapidly gaining traction in many areas of experimental molecular science for elucidating relationships and patterns in large or complex data sets. Historically, ML was largely the preserve of those with specialized training i...

Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression.

ACS nano
Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpre...

Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept.

Scientific reports
The major prevalent primary bone cancer is osteosarcoma. Preoperative chemotherapy is accompanied by resection as part of the normal course of treatment. The diagnosis and treatment of patients are based on the chemotherapy reaction. Contrarily, chem...

Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.

BMC psychiatry
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences ...

Machine Learning Analysis of Single-Voxel Proton MR Spectroscopy for Differentiating Solitary Fibrous Tumors and Meningiomas.

NMR in biomedicine
Solitary fibrous tumor (SFT), formerly known as hemangiopericytoma, is an uncommon brain tumor often confused with meningioma on MRI. Unlike meningiomas, SFTs exhibit a myoinositol peak on magnetic resonance spectroscopy (MRS). This study aimed to de...

Hierarchical clustering analysis & machine learning models for diagnosing skeletal classes I and II in German patients.

BMC oral health
BACKGROUND: Classification is one of the most common tasks in artificial intelligence (AI) driven fields in dentistry and orthodontics. The AI abilities can significantly improve the orthodontist's critical mission to diagnose and treat patients prec...