AIMC Topic: Least-Squares Analysis

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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectroscopy offers rapid and cost-effective acquisition of vibrational spectral data characteristic of prote...

Noise-resistant predefined-time convergent ZNN models for dynamic least squares and multi-agent systems.

Neural networks : the official journal of the International Neural Network Society
Zeroing neural networks (ZNNs) are commonly used for dynamic matrix equations, but their performance under numerically unstable conditions has not been thoroughly explored, especially in situations involving unequal row-column matrices. The challenge...

Machine learning-based multi-pool Voigt fitting of CEST, rNOE, and MTC in Z-spectra.

Magnetic resonance in medicine
PURPOSE: Four-pool Voigt (FPV) machine learning (ML)-based fitting for Z-spectra was developed to reduce fitting times for clinical feasibility in terms of on-scanner analysis and to promote larger cohort studies. The approach was compared to four-po...

Machine learning and chemometric methods for high-throughput authentication of 53 Root and Rhizome Chinese Herbal using ATR-FTIR fingerprints.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
To address the identification challenges caused by morphological similarities in Root and Rhizome Chinese Herbal (RRCH), this study developed a discrimination system integrating Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (AT...

The fluorescence spectrum combined with a broad learning system to characterize the content of difenoconazole in cabbage.

Analytical methods : advancing methods and applications
Pesticide residue detection plays an important role in vegetable quality and food safety. In this work, we propose a method for detecting difenoconazole pesticide residues based on fluorescence spectroscopy technology and machine learning algorithms....

Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.

Scientific reports
Alzheimer's disease (AD) is the most prevalent type of dementia. It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early d...

Comparison of individualized facial growth prediction models using artificial intelligence and partial least squares based on the Mathews growth collection.

The Angle orthodontist
OBJECTIVES: To develop facial growth prediction models using artificial intelligence (AI) under various conditions, and to compare performance of these models with each other as well as with the partial least squares (PLS) growth prediction model.

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...

Rapid evaluation of Pixian Douban meju in the tank fermentor Based on the image features and multi-model analysis.

Journal of food science
Pixian Douban (PXDB) meju is a crucial intermediate product in the PXDB production. In this study, a machine vision system was employed to monitor and evaluate the meju quality quickly to replace the time-consuming chemical methods. The results of co...

Deconvolution of spatial transcriptomics data via graph contrastive learning and partial least square regression.

Briefings in bioinformatics
Deciphering the cellular abundance in spatial transcriptomics (ST) is crucial for revealing the spatial architecture of cellular heterogeneity within tissues. However, some of the current spatial sequencing technologies are in low resolutions, leadin...