AIMC Topic: Machine Learning

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Deep structural clustering reveals hidden systematic biases in RNA sequencing data.

Genome research
RNA sequencing (RNA-seq) is a pivotal tool for transcriptomic analysis, providing comprehensive exploration of gene expression across diverse biological contexts. However, RNA-seq data are susceptible to various biases that can significantly compromi...

Machine learning models for predicting renal injury in patients with gout.

Renal failure
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.

From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy.

World journal of urology
OBJECTIVE: Percutaneous nephrolithotomy is the gold standard for treating large kidney stones. However, traditional scoring systems and logistic regression-based models have limited predictive power due to their reliance on linear assumptions. This s...

Molecular signature evolution of dissolved organic matter in wastewater during far-ultraviolet/peracetic acid disinfection: Integrated characterization and machine learning.

Water research
A far-ultraviolet/peracetic acid (UV222/PAA) disinfection process was developed in this study to investigate the transformation mechanisms of dissolved organic matter (DOM) in wastewater, via an integrated approach combining comprehensive molecular c...

Machine learning-assisted aroma profile prediction in tomato puree based on flavoromics.

Food chemistry
Flavor serves as a key quality indicator in tomato puree (TP) processing; however, conventional methods often fall short in providing rapid and accurate assessments. To address this limitation, this study integrated flavoromics with machine learning ...

Self-regulating microfluidic system for lipid nanoparticle production.

Journal of controlled release : official journal of the Controlled Release Society
Lipid nanoparticles have emerged as valuable gene delivery systems paving the way for next-generation vaccine and cancer therapeutics. Inevitably, this evolution is carried by dissecting and rationalizing the vehicles' complex formulation process. Gi...

Exploring multidrug resistance patterns in community-acquired urinary tract infections with machine learning.

Antimicrobial agents and chemotherapy
While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remain underexplored. This study used association-set mining to explore resistance associations within i...

Study on the Adsorption Performance of Ionic Liquids Based on Molecular Dynamics and Interpretable Machine Learning.

Journal of chemical information and modeling
The stable adsorption behavior of ionic liquid lubricants at metal interfaces is a key mechanism for achieving their excellent friction-reducing and antiwear properties. This study employs a research strategy that combines high-throughput molecular d...

Learning Binding Affinities via Fine-Tuning of Protein and Ligand Language Models.

Journal of chemical information and modeling
Accurate in silico prediction of protein-ligand binding affinity is essential for efficient hit identification in large molecular libraries. Commonly used structure-based methods such as docking often fail to rank compounds effectively, and free ener...

Decoding climate-induced phytoplankton dynamics in a tropical macrotidal estuary using explainable machine learning.

The Science of the total environment
Phytoplankton communities in tropical macrotidal estuaries are highly sensitive to hydroclimatic variability, particularly during extreme El Niño-Southern Oscillation (ENSO) events. This study assessed ENSO effects on phytoplankton dynamics in the Sã...