AIMC Topic: Female

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Digitally Enabled AI-Interpreted Salivary Ferning-Based Ovulation Prediction: Feasibility Study.

Journal of medical Internet research
BACKGROUND: Females with irregular or unpredictable cycles, including those with polycystic ovary syndrome (PCOS), have limited options for validated at-home ovulation prediction. The majority of over-the-counter ovulation prediction kits use urinary...

Innovative machine learning approach for liver fibrosis and disease severity evaluation in MAFLD patients using MRI fat content analysis.

Clinical and experimental medicine
This study employed machine learning models to quantitatively analyze liver fat content from MRI images for the evaluation of liver fibrosis and disease severity in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). A total o...

Automated classification of skeletal malocclusion in German orthodontic patients.

Clinical oral investigations
OBJECTIVES: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differen...

Bioinformatics analysis of Rho-signal transduction genes in postmenopausal osteoporosis and periodontitis.

Scientific reports
Postmenopausal osteoporosis (PMOP) increases the risk of periodontitis (PD), yet the shared mechanisms remain unclear. Rho-signal transduction genes may play a role due to their involvement in bone remodeling. This study aimed to explore Rho-related ...

Leveraging deep learning for the detection of socially desirable tendencies in personnel selection: A proof-of-concept.

PloS one
We propose a deep learning-based method for detecting Socially Desirable Responding (SDR)-the tendency for individuals to distort questionnaire responses to present themselves in a favorable light. Our objective is to showcase that such novel methods...

Machine learning-based predictive modeling of angina pectoris in an elderly community-dwelling population: Results from the PoCOsteo study.

PloS one
BACKGROUND: Angina pectoris, a comparatively common complaint among older adults, is a critical warning sign of underlying coronary heart disease. We aimed to develop machine learning-based models using multiple algorithms to predict and identify the...

Natural language processing for kidney ultrasound analysis: correlating imaging reports with chronic kidney disease diagnosis.

Renal failure
INTRODUCTION: Natural language processing (NLP) has been used to analyze unstructured imaging report data, yet its application in identifying chronic kidney disease (CKD) features from kidney ultrasound reports remains unexplored.

Personalized colorectal cancer risk assessment through explainable AI and Gut microbiome profiling.

Gut microbes
The clinical adenoma - carcinoma progression represents a well-established framework for understanding colorectal cancer (CRC) development, although the molecular mechanisms underlying this transition remain only partially understood. Increasing evid...

Integrative transcriptomic analysis reveals oligodendrocyte lineage switching in multiple sclerosis.

Life science alliance
Multiple sclerosis (MS) is a chronic disease of the central nervous system. The occurrence of MS is a phased process while its cause is still unclear. Here, by combining white matter single-nucleus transcriptomic datasets from MS and control samples,...

The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods.

BMC infectious diseases
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.