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Identification of Phosphodiesterase type 5 inhibitors (PDE5is) analogues using surface-enhanced Raman scattering and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Phosphodiesterase type 5 inhibitors (PDE5is), primarily used for the treatment of erectile dysfunction, have been severely misused in recent years, posing a threat to public health and safety. This study developed a method that combines Surface-enhan...

A density-based MS disease diagnosis model using the capuchin search algorithm and an ensemble of deep neural networks.

Scientific reports
Multiple sclerosis (MS) is a severe brain disease that permanently destroys brain cells, impacting vision, balance, muscle control, and daily activity. This research employs a weighted combination of deep neural networks and optimization techniques f...

Differentiation of glioblastoma G4 and two types of meningiomas using FTIR spectra and machine learning.

Analytical biochemistry
Brain tumors are among the most dangerous, due to their location in the organ that governs all life processes. Moreover, the high differentiation of these poses a challenge in diagnostics. Therefore, this study focused on the chemical differentiation...

Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...

Integrating EPSOSA-BP neural network algorithm for enhanced accuracy and robustness in optimizing coronary artery disease prediction.

Scientific reports
Coronary artery disease represents a formidable health threat to middle-aged and elderly populations worldwide. This research introduces an advanced BP neural network algorithm, EPSOSA-BP, which integrates particle swarm optimization, simulated annea...

Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in saliva can provide an alternative for drug analysis in forensic toxicology. Therefore, a highly sensitive, fast, reagent-free, and sustainable approach wi...

Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the environment in the surface aquatic ecosystem. The widespread use of antibiotics has resulted in serious ...

Predicting purification process fit of monoclonal antibodies using machine learning.

mAbs
In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purifi...

Unveiling neural activity changes in mild cognitive impairment using microstate analysis and machine learning.

Journal of Alzheimer's disease : JAD
BACKGROUND: Mild cognitive impairment (MCI) is recognized as a condition that may increase the risk of developing Alzheimer's disease (AD). Understanding the neural correlates of MCI is crucial for elucidating its pathophysiology and developing effec...

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Journal of proteome research
Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic analyses of PPD-risk women remain limited. This study analyzed plasma samples from 30 healthy postpartum women and 30 PPD-risk women using mass spectrome...