AIMC Topic: Machine Learning

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Leveraging machine learning and single-cell RNA sequencing strategies to develop a risk prognosis scoring based on liquid-liquid phase separation feature genes in pediatric hepatoblastoma.

Computers in biology and medicine
BACKGROUND: Considerable evidence highlights the intricate association between liquid-liquid phase separation (LLPS) and tumorigenesis, progression, and therapy resistance. However, there has been limited exploration of the role of LLPS in hepatoblas...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Computers in biology and medicine
Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher susceptibility to fractures, even in response to minimal trauma. Osteoporotic fractures represent a...

An integrated approach for key gene selection and cancer phenotype classification: Improving diagnosis and prediction.

Computers in biology and medicine
The identification of key features and reliable phenotype classification remains pivotal in cancer research, with direct implications for early diagnosis, prognosis, treatment optimization, and cost reduction in healthcare. This study introduces a hy...

Prediction of bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) for per- and polyfluoroalkyl substances (PFASs) using Read-Across and q-RASPR.

The Science of the total environment
Per- and polyfluoroalkyl substances (PFASs) contamination poses an environmental concern due to their ability to bioaccumulate in aquatic species and adversely impact human health. Experimental bioconcentration factor (log BCF) data of freshwater fis...

Predicting the impact of climate warming on soil quality using bacteria and machine learning.

Journal of environmental management
In the context of global warming, a substantial portion of global soil is in a state of degradation, which poses a significant threat to biodiversity and food production worldwide. Moreover, monitoring soil quality typically requires measuring numero...

Dosing prediction of valproic acid in pediatric patients with epilepsy: population pharmacokinetic model or machine learning model?

European journal of clinical pharmacology
PURPOSE: This study develops and compares population pharmacokinetics (PopPK) models and machine learning methods, including neural networks, to predict steady-state trough concentrations in pediatric patients and provide improved dosing recommendati...

Machine learning-driven prediction of eye irritation toxicity: Integration of in silico and in vitro study.

Toxicology and applied pharmacology
Eye irritation (EI) toxicity poses critical challenges in chemical safety assessment, demanding alternatives to ethically contentious animal testing. We present the first integrative framework combining computational prediction with experimental vali...

EnsemPred-ACP: Combining machine and deep learning to improve anticancer peptide prediction.

Computers in biology and medicine
Anticancer peptide (ACP) has emerged as potent therapeutic agents owing to its ability to selectively target cancer cells while minimising toxicity to healthy cells. However, the accurate computational prediction of ACP remains challenging because of...

Advancing breast cancer prediction using blockchain-secured hybrid genetic algorithm.

Computers in biology and medicine
Feature selection using evolutionary algorithms-a well-liked technique for choosing pertinent characteristics in huge datasets is explored. In machine learning, feature selection (FS) is a key phase that helps to boost model efficiency, decrease over...

Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.

Molecular medicine reports
Ferroptosis and lethal sepsis are interlinked, although this association remains largely unknown to clinical panels. Sepsis is characterized by dysfunction of the inflammatory microenvironment. Most septic biomarkers lack independent validation, and ...