AIMC Topic: Female

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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...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Computers in biology and medicine
Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contributions remain poorly understood. This study aimed to identify inflammation-related biomarkers for d...

Association between prenatal exposure to per- and polyfluoroalkyl substances and blood pressure among preschool-aged children: The moderating effect of child-age and the mediating effect of inflammatory cytokine.

Ecotoxicology and environmental safety
Our aim is to evaluate the association of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with offspring blood pressure (BP); examine the moderating effect of children's age; and the mediating effects of inflammatory cytokines. Data o...

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...

Developing a Panel of Shared Susceptibility Genes as Diagnostic Biomarkers for chronic obstructive pulmonary disease and Heart Failure.

Computers in biology and medicine
AIM: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) are closely intertwined comorbidities that present significant clinical challenges due to the poorly understood pathophysiological mechanisms driving their coexistence. In this ...

Computer vision for automatic identification of blastocyst structures and blastocyst formation time in In-Vitro Fertilization.

Computers in biology and medicine
Embryo selection is an indispensable step to ensure the success of In-Vitro Fertilization; however, this decision is a time-consuming, laborious, and highly subjective task for embryologists. In the best scenarios, when implanting an embryo of the be...

Transformer attention-based neural network for cognitive score estimation from sMRI data.

Computers in biology and medicine
Accurately predicting cognitive scores based on structural MRI holds significant clinical value for understanding the pathological stages of dementia and forecasting Alzheimer's disease (AD). Some existing deep learning methods often depend on anatom...

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...

Efficient sleep apnea detection using single-lead ECG: A CNN-Transformer-LSTM approach.

Computers in biology and medicine
BACKGROUND: Sleep apnea (SA), a prevalent sleep-related breathing disorder, disrupts normal respiratory patterns during sleep. This disruption can have a cascading effect on the body, potentially leading to complications in various organs, including ...

Deep learning framework for cardiorespiratory disease detection using smartphone IMU sensors.

Computers in biology and medicine
Respiratory and cardiovascular diseases represent a significant global health burden, underscoring the need for innovative, accessible, and cost-effective screening solutions. This study introduces a clinically grounded framework for the early detect...