AIMC Topic: Female

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Gut microbiota predictive of the efficacy of consolidation immunotherapy and chemoradiotherapy toxicity in lung cancer.

Med (New York, N.Y.)
BACKGROUND: Gut microbiota (GM) predict responses to immune checkpoint inhibitors (ICIs) in patients with advanced lung cancer. However, its role in patients with locally advanced lung cancer undergoing chemoradiotherapy (CRT) combined with consolida...

Integrated Chemical Array and SERS Profiling of Plasma Small Extracellular Vesicles for Breast Cancer Diagnosis.

Nano letters
Small extracellular vesicles (sEVs) are nanoscale vesicles carrying biomolecules reflective of their cellular origin, making them attractive biomarkers for cancer diagnosis. In this study, we present a high-throughput strategy integrating amphiphile-...

Mapping subnational gender gaps in internet and mobile adoption using social media data.

Proceedings of the National Academy of Sciences of the United States of America
The digital revolution has ushered in many societal and economic benefits. Yet access to digital technologies such as mobile phones and internet remains highly unequal, especially by gender in the context of low- and middle-income countries (LMICs). ...

Prevalence, associated factors, and machine learning-based prediction of depression, anxiety, and stress among university students: a cross-sectional study from Bangladesh.

Journal of health, population, and nutrition
BACKGROUND: Mental health challenges are a growing global public health concern, with university students at elevated risk due to academic and social pressures. Although several studies have exmanined mental health among Bangladeshi students, few hav...

Gene association study between polycystic ovary syndrome and metabolic syndrome: a transcriptomic analysis and machine learning approach.

Journal of ovarian research
BACKGROUND: Patients with polycystic ovary syndrome (PCOS) often experience a range of metabolic comorbidities, suggesting a potential association between PCOS and metabolic syndrome (MetS). However, this potential link has not yet been fully elucida...

Computational pathology approach for assessment of prognosis and immunotherapy response in pan-gastrointestinal cancer.

Journal of translational medicine
BACKGROUND: Current cancer staging methods cannot accurately predict survival outcomes and therapeutic benefits in cancer patients. Digital pathomics, a rapidly evolving field, holds significant potential to revolutionize disease evaluation.

Validity and reliability analysis of the Turkish life satisfaction scale developed through artificial intelligence.

BMC psychology
This study evaluates the validity and reliability of a Turkish Life Satisfaction Scale developed using artificial intelligence (ChatGPT) to explore AI's potential in creating psychometric tools. The scale was tested on three independent samples of Tu...

Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX.

Breast cancer research : BCR
BACKGROUND: Proper stratification of recurrence risk in breast cancer is crucial for guiding treatment decisions. This study aims to predict the recurrence risk of breast cancer patients using a multimodal deep learning model that integrates multiple...

Development and validation of artificial intelligence models for automated periodontitis staging and grading using panoramic radiographs.

BMC oral health
BACKGROUND: Periodontal diseases are common chronic conditions that can lead to tooth loss and systemic complications if not diagnosed and treated promptly. The 2017 classification by the American Academy of Periodontology highlights the need for eff...

Feasibility of machine learning analysis for the identification of patients with possible primary ciliary dyskinesia.

Orphanet journal of rare diseases
BACKGROUND: Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening methods could improve early identification and health outcomes.