AIMC Topic: Female

Clear Filters Showing 23831 to 23840 of 29210 articles

AI in Hypertensive Disorders of Pregnancy: Review.

American journal of hypertension
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are a leading cause of maternal and fetal mortality worldwide. Early detection and risk stratification are critical for timely intervention to prevent severe complications such as eclampsia, strok...

The Maternal Blood Transcriptome Reflects Changes in Fetal Growth and Is an Accurate Predictor of Birth Weight in Cattle.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Harnessing information from maternal blood to predict fetal growth is an emerging area of research in livestock production, offering a noninvasive tool to monitor development. This study aimed to investigate temporal changes in blood gene expression ...

Decoding Dendritic Cell Subtypes via Integrated Radiogenomics: A Stacked Ensemble Model for Predicting Immunotherapy Response in NSCLC.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
We pioneer a multimodal framework integrating single-cell RNA sequencing (scRNA-seq), radiomics, and deep learning to decipher dendritic cell (DC)-mediated mechanisms underlying anti-PD-1 response in non-small cell lung cancer (NSCLC). Single-cell RN...

Stereotactic Radiation Therapy or Protons for Uveal Melanoma Patients? An Artificial Intelligence (AI)-Based Clinical Treatment Decision-Making Tool Predicting Doses To Radiation Therapy Constraints.

International journal of radiation oncology, biology, physics
PURPOSE: For ocular melanoma, selecting between stereotactic radiation therapy (SRT) and protons requires a lengthy plan comparison process. The purpose of this brief report is to describe an artificial intelligence (AI) decision-making tool to predi...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

Journal of affective disorders
BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning mo...

From quality of life to sleep quality in Chinese college students: stress and anxiety as sequential mediators with nonlinear effects via machine learning.

Journal of affective disorders
OBJECT: This study examines how quality of life is associated with sleep quality among Chinese university students through sequential mediation by perceived stress and sleep anxiety, using machine learning to uncover nonlinear effects.

Machine learning identifies prominent risk factors for depressive symptoms among Chinese children and adolescents.

Journal of affective disorders
BACKGROUND: Identifying key risk factors for depressive symptoms in children and adolescents is crucial for prevention. However, few studies have explored this topic. This study aimed to examine the prevalence of depressive symptoms in Chinese childr...

Enhancing differentiation between unipolar and bipolar depression through integration of machine learning and electroencephalogram analysis.

Journal of affective disorders
To enhance the differentiation between unipolar depression (UPD) and bipolar depression (BPD), this study integrates machine learning and deep learning models with electroencephalography (EEG) data and clinical features. Utilizing Python for data pre...

Discovering the metabolic pathway of liver disease by breath mass spectrometry combined with machine learning.

Journal of pharmaceutical and biomedical analysis
On account of the low concentration and complex background, most methods for detecting VOCs in exhaled breath samples required preconcentration prior to instrumental analysis. In the current study, a simple and rapid method is developed for analyzing...

Breast cancer early detection and molecular subtype prediction by combination of Raman spectroscopy with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Breast cancer is one of the most common tumors in women, and early screening can significantly reduce mortality rates. Meanwhile, accurately identifying HER2-positive and HER2-negative subtypes of breast cancer is critical for helping doctors determi...