AIMC Topic: Female

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Exploring educational hypogamy among women in urban and rural China: Insights from random forest machine learning.

PloS one
BACKGROUND: Educational hypogamy, where women marry men with lower educational attainment, reflects evolving gender roles and societal norms. In China, the rapid expansion of education, coupled with persistent traditional values, provides a unique co...

When automation hits jobs: Entrepreneurship as an alternative career path.

PloS one
This study investigates the relationship between occupational automation risks and workers' transitions to entrepreneurship using data from the Current Population Survey. We find that employees facing automation-related job displacement are inclined ...

Machine learning-based prediction model for 28-day mortality in acute kidney injury patients with liver cirrhosis: A MIMIC-IV database analysis.

PloS one
BACKGROUND: Acute kidney injury (AKI) in patients with liver cirrhosis represents a significant clinical challenge with high mortality rates. This study aimed to develop and validate a machine learning-based prediction model for 28-day mortality in A...

Comparative analysis of cervical cancer classification of DPAGCHE-enhanced Pap smear images using convolutional neural network models.

PloS one
Cervical cancer remains a significant cause of female mortality worldwide, primarily due to abnormal cell growth in the cervix. This study proposes an automated classification method to enhance detection accuracy and efficiency, addressing contrast a...

Artificial intelligence-based CT histogram parameters differentiating bronchiolar adenoma and lung adenocarcinomas: A two-center study.

PloS one
PURPOSE: Bronchiolar adenoma (BA) is a rare benign pulmonary neoplasm originating from the bronchial mucosal epithelium and mimics lung adenocarcinoma (LAC) both radiographically and microscopically. This study aimed to develop a nomogram for disting...

Artificial Intelligence Automation of Echocardiographic Measurements.

Journal of the American College of Cardiology
BACKGROUND: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intel...

Performance evaluation of machine learning models in cervical cancer diagnosis: Systematic review and meta-analysis.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: Cervical cancer is one of the most frequent malignancies worldwide and one of the leading causes of death in women. Recently, artificial intelligence-based tools have been developed for the early diagnosis of malignancies, including cer...

Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Transportation insecurity is a known barrier to accessing eye care and is associated with poorer visual outcomes for patients. However, its mention is seldom captured in structured data fields in electronic health records, limiting effort...

Syllable-based speech characteristics as potential biomarker for differential diagnosis of Parkinson's disease, multiple system atrophy, and cerebellar ataxia.

Journal of neurology
Speech disorders differ between Parkinson's disease (PD) and multiple system atrophy (MSA), but studies focusing on group differences based on syllables or including cerebellar ataxia (CA) are lacking until now. This cross-sectional study aimed to an...

Machine learning for the prediction of blood transfusion risk during or after mitral valve surgery: a multicenter retrospective cohort study.

Scientific reports
This study aimed to identify the optimal prediction method and key preoperative variables for red blood cell (RBC) transfusion risk in patients undergoing mitral valve surgery. We conducted a retrospective study involving 1477 patients from eight lar...