Primary Care

Machine learning applications in preventive healthcare: A systematic literature review on predictive analytics of disease comorbidity from multiple perspectives.

Artificial intelligence is constantly revolutionizing biomedical research and healthcare management. Disease comorbidity is a major threat to the quality of life for susceptible groups, especially middle-aged and elderly patients. The presence of multiple chronic diseases makes precision diagnosis challenging to realize and imposes a heavy burden on the healthcare system and economy. Given an enor...

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in models performing poorly in predicting minority classes, affecting overall diagnostic performance.

Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression.

The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this...

A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension.

The diagnosis and treatment of pulmonary hypertension have changed dramatically through the re-defined diagnostic criteria and advanced drug developme...

Spatial source, simulating improvement, and short-term health effect of high PM exposure during mutation event in the key urban agglomeration regions in China.

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused b...

Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification.

Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the incorporation of hair minerals into ML models remai...

From bytes to nephrons: AI's journey in diabetic kidney disease.

Diabetic kidney disease (DKD) is a significant complication of type 2 diabetes, posing a global health risk. Detecting and predicting diabetic kidney ...

Deep learning radiomics based on ultrasound images for the assisted diagnosis of chronic kidney disease.

AIM: This study aimed to explore the value of ultrasound (US) images in chronic kidney disease (CKD) screening by constructing a CKD screening model b...

Machine learning of Raman spectra predicts drug release from polysaccharide coatings for targeted colonic delivery.

Colonic drug delivery offers numerous pharmaceutical opportunities, including direct access to local therapeutic targets and drug bioavailability bene...

Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension.

INTRODUCTION: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients.

Simulated arbitration of discordance between radiologists and artificial intelligence interpretation of breast cancer screening mammograms.

Artificial intelligence (AI) algorithms have been retrospectively evaluated as replacement for one radiologist in screening mammography double-reading...

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.

: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine t...

Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis.

There is no effective fall risk screening tool for the elderly that can be integrated into clinical practice. Developing a system that can be easily u...

Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.

BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Dia...

Learning control-ready forecasters for Blood Glucose Management.

Type 1 diabetes (T1D) presents a significant health challenge, requiring patients to actively manage their blood glucose (BG) levels through regular b...

Identification of COL3A1 as a candidate protein involved in the crosstalk between obesity and diarrhea using quantitative proteomics and machine learning.

BACKGROUND: Increasing epidemiologic studies have shown a positive correlation between obesity and chronic diarrhea. Nevertheless, the precise etiolog...

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyp...

The Role of Preoperative Abdominal Ultrasound in the Preparation of Patients Undergoing Primary Metabolic and Bariatric Surgery: A Machine Learning Algorithm on 4418 Patients' Records.

BACKGROUND: The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) re...

A risk prediction model based on machine learning algorithm for parastomal hernia after permanent colostomy.

OBJECTIVE: To develop a machine learning-based risk prediction model for postoperative parastomal hernia (PSH) in colorectal cancer patients undergoin...

Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.

According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are r...