AIMC Topic: Female

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Non-coding genetic elements of lung cancer identified using whole genome sequencing in 13,722 Chinese.

Nature communications
A substantial portion of lung cancer-associated genetic elements in East Asian populations remains unidentified, underscoring the need for large-scale genome-wide studies, particularly on non-coding regulation. We conducted a whole genome sequencing ...

Ligand supplementation restores the cancer therapy efficacy of the antirheumatic drug auranofin from serum inactivation.

Nature communications
Auranofin, an FDA-approved antirheumatic gold drug, has gained ongoing interest in clinical studies for treating advanced or recurrent tumors. However, gold ion's dynamic thiol exchange nature strongly attenuates its bioactivity due to the fast forma...

Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.

Scientific reports
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...

Unveiling social determinants of health impact on adverse pregnancy outcomes through natural language processing.

Scientific reports
Understanding the role of Social Determinants of Health (SDoH) in pregnancy outcomes is critical for improving maternal and infant health yet extracting SDoH from unstructured electronic health records remains challenging. We trained and evaluated na...

Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.

Scientific reports
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...

Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Scientific reports
Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of tuberculosis preventive therapy (TPT) remains inadequately understood. Using observational data from 4152 HIV patients in Ethiopia (2005-2024), we appl...

WGCNA combined with machine learning for analysis of diagnostic markers of preeclampsia associated with the hedgehog signaling pathway.

Hypertension in pregnancy
BACKGROUND: Abnormal hedgehog (Hh) signaling is linked to preeclampsia (PE). This study aimed to identify Hh-related diagnostic biomarkers for PE and assess the role of immune infiltration.

Enhancing schizophrenia diagnosis efficiency with EEGNet: a simplified recognition model based on γ band features.

Psychiatry research. Neuroimaging
OBJECTIVE: This study aims to develop an objective and efficient diagnostic model for schizophrenia (SCZ) by integrating electroencephalogram (EEG) signals with deep learning techniques. Building on previous research, γ wave activity is selected as a...

Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study.

BMC medical informatics and decision making
BACKGROUND: Anti-programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunotherapy has revolutionized cancer treatment. However, it can cause immune-related adverse events, including acute kidney injury (AKI). Such adverse e...

Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods.

Scientific reports
COVID-19 has posed a significant global health challenge, affecting individuals across all age groups. While extensive research has focused on adults, pediatric patients exhibit distinct clinical characteristics that necessitate specialized predictiv...