Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning.

BACKGROUND: Early identification of high-risk individuals for weight problems in children and adoles...

Screening COPD-Related Biomarkers and Traditional Chinese Medicine Prediction Based on Bioinformatics and Machine Learning.

PURPOSE: To employ bioinformatics and machine learning to predict the characteristics of immune cell...

Artificial intelligence and forensic mental health in Africa: a narrative review.

This narrative review examines the integration of Artificial Intelligence (AI) tools into forensic p...

Enhancing pharmacist intervention targeting based on patient clustering with unsupervised machine learning.

OBJECTIVES: Adherence to the American Diabetes Association (ADA) Standards of Medical Care is low. T...

Artificial intelligence and psychedelic medicine.

Artificial intelligence (AI) and psychedelic medicines are among the most high-profile evolving disr...

A Machine Learning Algorithm Suggests Repurposing Opportunities for Targeting Selected GPCRs.

Repurposing utilizes existing drugs with known safety profiles and discovers new uses by combining e...

Self-monitoring of Oral Health Using Smartphone Selfie Powered by Artificial Intelligence: Implications for Preventive Dentistry.

PURPOSE: With the increasing use of artificial intelligence (AI) in dentistry, it is feasible to sel...

Highly Sensitive Perovskite Photoplethysmography Sensor for Blood Glucose Sensing Using Machine Learning Techniques.

Accurate non-invasive monitoring of blood glucose (BG) is a challenging issue in the therapy of diab...

Identification of Nocturnal Leg Cramps and Affecting Factors in COPD Patients: Logistic Regression and Artificial Neural Network.

Although there are many sleep-related complaints in chronic obstructive pulmonary disease (COPD) pat...

Nuclear magnetic resonance-based metabolomics with machine learning for predicting progression from prediabetes to diabetes.

BACKGROUND: Identification of individuals with prediabetes who are at high risk of developing diabet...

Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mo...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artif...

Predicting Antidiabetic Peptide Activity: A Machine Learning Perspective on Type 1 and Type 2 Diabetes.

Diabetes mellitus (DM) presents a critical global health challenge, characterized by persistent hype...

Development and validation of a machine learning-based framework for assessing metabolic-associated fatty liver disease risk.

BACKGROUND: The existing predictive models for metabolic-associated fatty liver disease (MAFLD) poss...

Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes compl...

[Development and validation of a tool for the systematic identification of social vulnerabilities in cancer patients: the DEFCO tool].

INTRODUCTION: Literature suggests that patients from deprived backgrounds are less likely to adhere ...

Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction.

In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting p...

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