AIMC Topic: Female

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Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records.

Scientific reports
Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing ...

Development and validation of a nomogram model to predict postoperative delirium after resection of esophageal cancer.

Scientific reports
The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) among esophageal cancer resection patients. Clinical data of 396 patients with esophageal cancer who underwent esophagectomy from November 2020 to June...

Accuracy and acceptability of self-sampling HPV testing in cervical cancer screening: a population-based study in rural Yunnan, China.

Scientific reports
To evaluate the accuracy and acceptability of self-sampling samples for HPV testing for cervical cancer screening in rural Yunnan of China. In 2022, 3000 women aged 17-69 were recruited and provided self-sampling vaginal samples alongside provider-sa...

Prevalence of malnutrition and associated factors in Chinese children and adolescents aged 3-14 years using machine learning algorithms.

Journal of global health
BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential t...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

An illustration of multi-class roc analysis for predicting internet addiction among university students.

PloS one
The internet is one of the essential tools today, and its impact is particularly felt among university students. Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the p...

Quantitative modeling of mortality patterns in dogs exposed to alpha particle emitting radionuclides: Insights from competing risks and causal inference machine learning.

PloS one
This study employed state-of-the-art machine learning to evaluate the mortality effects of alpha-emitting radionuclides (241Am, 249Cf, 252Cf, 238Pu, 239Pu, 224Ra, 226Ra, 228Th) on 2,576 dogs, factoring in radioactivity levels, composition, administra...

Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma.

PloS one
Chloride channel accessory 1 (CLCA1) is considered a potential prognostic biomarker for colon adenocarcinoma (COAD). The objective of this research was to develop two pathomics models to predict CLCA1 expression from hematoxylin-eosin (H&E) stained p...

Identification of podocyte molecular markers in diabetic kidney disease via single-cell RNA sequencing and machine learning.

PloS one
Diabetic kidney disease (DKD) is a major cause of end-stage renal disease globally, with podocytes being implicated in its pathogenesis. However, the underlying mechanisms of podocyte involvement remain unclear. The aim of the present study was to id...

Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models.

PloS one
OBJECTIVES: Predicting optimal coagulation control using heparin in intensive care units (ICUs) remains a significant challenge. This study aimed to develop a machine learning (ML) model to predict activated partial thromboplastin time (aPTT) in ICU ...