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Predicting abnormal C-reactive protein level for improving utilization by deep neural network model.

International journal of medical informatics
BACKGROUND: C-reactive protein (CRP) is an inflammatory biomarker frequently used in clinical practice. However, insufficient evidence-based ordering inevitably results in its overuse or underuse. This study aims to predict its normal and abnormal le...

Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.

Scientific reports
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...

Machine-Learning-Based Predictive Model for Bothersome Stress Urinary Incontinence Among Parous Women in Southeastern China.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: Accurate identification of female populations at high risk for urinary incontinence (UI) and early intervention are potentially effective initiatives to reduce the prevalence of UI. We aimed to apply machine-learning tech...

An Application of Machine-Learning-Oriented Radiomics Model in Clear Cell Renal Cell Carcinoma (ccRCC) Early Diagnosis.

British journal of hospital medicine (London, England : 2005)
Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of kidney cancer, where early diagnosis is crucial for improving prognosis and treatment outcomes. Radiomics, which utilizes machine learning techniques, presents a promising ap...

Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment.

Scientific reports
This bicenter retrospective analysis included 162 patients who had undergone prostate biopsy following prebiopsy MRI, excluding those with PCa identified only in the peripheral zone (PZ). DLR T2WI achieved a 69% reduction in scan time relative to TSE...

Human essential gene identification based on feature fusion and feature screening.

IET systems biology
Essential genes are necessary to sustain the life of a species under adequate nutritional conditions. These genes have attracted significant attention for their potential as drug targets, especially in developing broad-spectrum antibacterial drugs. H...

Establishing a machine learning dementia progression prediction model with multiple integrated data.

BMC medical research methodology
OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical tools for predicting the progression of degenerative dementia are highly valuable. Machine learning (ML) methods facilitate the construction of effec...

Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Accurate hospital length of stay (LoS) prediction enables efficient resource management. Conventional LoS prediction models with limited covariates and nonstandardized data have limited reproducibility when applied to the general populati...

Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress.

BMC cancer
BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies investigating the relationship between oxidative stress and prognosis of elderly patients with esophagea...