AIMC Topic: Machine Learning

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Integrated machine learning and deep learning-based virtual screening framework identifies novel natural GSK-3β inhibitors for Alzheimer's disease.

Journal of computer-aided molecular design
Alzheimer's disease (AD) is a progressive neurodegenerative disorder lacking effective therapies. Glycogen synthase kinase-3β (GSK-3β), a key regulator of Aβ aggregation and Tau hyperphosphorylation, has emerged as a promising therapeutic target. Her...

Machine learning prediction of DOC-water partitioning coefficients for organic pollutants from diverse DOM origins.

Environmental science. Processes & impacts
This study aims to improve predictions and understanding of dissolved organic carbon-water partitioning coefficients (), a crucial parameter in environmental risk assessment. A dataset encompassing 709 datapoints across 190 unique organic pollutants ...

Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.

PloS one
Electronic payment methods are increasingly prevalent worldwide, facilitating both in-person and online transactions. As credit card usage for online payments grows, fraud and payment defaults have also risen, resulting in significant financial losse...

Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

PloS one
BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often...

Spectral markers and machine learning: Revolutionizing Rice evaluation with near infrared spectroscopy.

Food chemistry
The evaluation of rice varieties is a complex, time-consuming process requiring advanced equipment. This study aimed to discriminate 22 commercial rice varieties from six types by analyzing biochemical, physicochemical, and cooking properties. Near-i...

Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning.

Cancer letters
Immunotherapy has become a cornerstone in the treatment of advanced gastric cancer (GC). However, identifying reliable predictive biomarkers remains a considerable challenge. This study demonstrates the potential of integrating multimodal baseline da...

Construction of a machine learning-based screening model for IgD myeloma.

Clinica chimica acta; international journal of clinical chemistry
OBJECTIVE: Immunoglobulin D (IgD) myeloma is a rare subtype of multiple myeloma (MM), comprising approximately 1 %-2 % of all MM cases. Owing to the diminished levels of IgD in serum, IgD MM manifests as subtle M protein spikes in routine serum elect...

Identification of high-risk hepatoblastoma in the CHIC risk stratification system based on enhanced CT radiomics features.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Survival of patients with high-risk hepatoblastoma remains low, and early identification of high-risk hepatoblastoma is critical.

Plasma Metabolomics and Machine Learning Reveals Metabolic Alterations and Diagnostic Biomarkers for Deep Venous Thrombosis in Hypertensive Patients after Traumatic Fracture.

Journal of proteome research
We aimed to explore the metabolic dysregulations and diagnostic biomarkers for post-traumatic deep venous thrombosis (pt-DVT) in hypertensive (HPT) patients after fracture. An untargeted ultraperformance liquid chromatography-mass spectrometry-based ...

Rapid Screening of Methicillin-Resistant Using MALDI-TOF MS and Machine Learning: A Randomized, Multicenter Study.

Analytical chemistry
Methicillin-resistant (MRSA) is a major cause of healthcare-associated infections including bacteremia. The rapid detection of MRSA is essential for prompt treatment and improved outcomes. However, traditional MRSA screening and confirmatory tests b...