AIMC Topic: Middle Aged

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Machine learning approaches for predicting heart failure readmissions.

Postgraduate medical journal
PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelihood of hospital readmission within 30 days after discharge for patients with heart failure (HF). The goal is to compare the predictive accuracy of ML ...

Stereotactic Radiation Therapy or Protons for Uveal Melanoma Patients? An Artificial Intelligence (AI)-Based Clinical Treatment Decision-Making Tool Predicting Doses To Radiation Therapy Constraints.

International journal of radiation oncology, biology, physics
PURPOSE: For ocular melanoma, selecting between stereotactic radiation therapy (SRT) and protons requires a lengthy plan comparison process. The purpose of this brief report is to describe an artificial intelligence (AI) decision-making tool to predi...

Enhancing differentiation between unipolar and bipolar depression through integration of machine learning and electroencephalogram analysis.

Journal of affective disorders
To enhance the differentiation between unipolar depression (UPD) and bipolar depression (BPD), this study integrates machine learning and deep learning models with electroencephalography (EEG) data and clinical features. Utilizing Python for data pre...

Discovering the metabolic pathway of liver disease by breath mass spectrometry combined with machine learning.

Journal of pharmaceutical and biomedical analysis
On account of the low concentration and complex background, most methods for detecting VOCs in exhaled breath samples required preconcentration prior to instrumental analysis. In the current study, a simple and rapid method is developed for analyzing...

Breast cancer early detection and molecular subtype prediction by combination of Raman spectroscopy with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Breast cancer is one of the most common tumors in women, and early screening can significantly reduce mortality rates. Meanwhile, accurately identifying HER2-positive and HER2-negative subtypes of breast cancer is critical for helping doctors determi...

Prognostic factors and prediction model for facial scar improvement in laser-treated patients: A machine learning-based retrospective cohort study.

Medicine
The face, being central and exposed, is highly susceptible to trauma and subsequent scar formation. Laser therapy is a common and effective treatment method for facial scars. However, treatment outcomes vary substantially. Consequently, we aimed to i...

Association and prediction of serum lipid profiles with incident stroke in the CHARLS cohort: A machine learning analysis.

Medicine
Using the 2011 baseline data of the China health and retirement longitudinal study, we examined the associations between serum lipids and other risk factors and incident stroke, and developed and compared multiple machine learning models for stroke-r...

Orthopedic perioperative nursing under navigation nurse management: Machine learning-based risk prediction models for postoperative recovery quality and explainable artificial intelligence analysis.

Medicine
This study aimed to evaluate the effectiveness of navigation nurse management (NNM) in orthopedic perioperative care and develop machine learning (ML) models to predict postoperative recovery quality. We sought to identify key factors influencing rec...

The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) as predictors of hypertensive patients: Analyses of NHANES data with machine learning.

Medicine
Elevated values of the non-HDL/HDL cholesterol ratio (NHHR) have been associated with increased hypertension risk, indicating its potential as a pathogenic factor, but its assessment remains challenging. We analyzed data from 22,562 hypertensive part...

Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models.

Medicine
Ureteroscopic lithotripsy has emerged as the cornerstone treatment modality for ureteral stones due to its exceptional success rates and minimal complication profiles. Nevertheless, postoperative urinary tract infection (UTI) remains a prevalent and ...