AIMC Topic: Humans

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Postpartum depression in Northeastern China: a cross-sectional study 6 weeks after giving birth.

Frontiers in public health
INTRODUCTION: Postpartum depression (PPD) is a prevalent mental health issue that poses significant challenges to maternal wellbeing and infant development. We aimed to determine the prevalence of PPD and to investigate its associated determinants an...

Resting-State Functional MRI Reveals Altered Seed-Based Connectivity in Diabetic Osteoporosis Patients.

Clinical interventions in aging
BACKGROUND: Diabetic osteoporosis (DOP) can cause abnormal brain neural activity, but its mechanism is still unclear. This study aims to further explore the abnormal functional connectivity between different brain regions based on the team's previous...

Time-series visual representations for sleep stages classification.

PloS one
Polysomnography is the standard method for sleep stage classification; however, it is costly and requires controlled environments, which can disrupt natural sleep patterns. Smartwatches offer a practical, non-invasive, and cost-effective alternative ...

Application of Generative AI to Enhance Obstetrics and Gynecology Research.

American journal of perinatology
The rapid evolution of large-language models such as ChatGPT, Claude, and Gemini is reshaping the methodological landscape of obstetrics and gynecology (OBGYN) research. This narrative review provides a comprehensive account of generative AI capabili...

Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity.

mBio
Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced by anticancer drugs, data from patients paired with careful side effect monitoring remains limited....

Exploring Hidden Dangers: Predicting Mycotoxin-like Toxicity and Mapping Toxicological Networks in Hepatocellular Carcinoma.

Journal of chemical information and modeling
Mycotoxins are potent triggers of hepatocellular carcinoma (HCC) due to their intricate interplay with cellular macromolecules and signaling pathways. This study integrates machine learning and biomolecular analyses to elucidate the mechanisms underl...

Constructing Built-In Electric Field in Hierarchical-Flower Heterostructure for High-Performance Serum Metabolic Assay.

Analytical chemistry
Laser desorption ionization mass spectrometry (LDI-MS) is a critical platform for high-throughput nontargeted metabolomics analysis in clinical diagnosis. However, traditional organic matrices inherently suffer from background interference in the low...

Assessing Physiological Stress Responses in Student Nurses Using Mixed Reality Training.

Sensors (Basel, Switzerland)
This study explores nursing students' stress responses while they are being trained in a mixed reality (MR) setting that replicates highly stressful clinical scenarios. Using measurements of physiological indices such as heart rate, electrodermal act...

Development of Non-Invasive Continuous Glucose Prediction Models Using Multi-Modal Wearable Sensors in Free-Living Conditions.

Sensors (Basel, Switzerland)
Continuous monitoring of glucose levels is important for diabetes management and prevention. While traditional glucose monitoring methods are often invasive and expensive, recent approaches using machine learning (ML) models have explored non-invasiv...

Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.

Sensors (Basel, Switzerland)
The physical workload evaluation of construction activities will help to prevent excess physical fatigue or overexertion. The workload determination involves measuring physiological responses such as oxygen uptake (VO) while performing the work. The ...