Primary Care

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

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Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines.

Precision, or personalized, medicine aims to stratify patients based on variable pathogenic signatur...

High performance COVID-19 screening using machine learning.

Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an ...

Investigation and Assessment of AI's Role in Nutrition-An Updated Narrative Review of the Evidence.

BACKGROUND: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition r...

Interpretable machine learning for identifying overweight and obesity risk factors of older adults in China.

OBJECTIVE: To estimate the importance of risk factors on overweight/obesity among older adults by co...

A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study.

Borderline personality disorder (BPD) is associated with a high risk of suicide. Despite several ris...

ECGEFNet: A two-branch deep learning model for calculating left ventricular ejection fraction using electrocardiogram.

Left ventricular systolic dysfunction (LVSD) and its severity are correlated with the prognosis of c...

Bioequivalence study of fluticasone propionate nebuliser suspensions in healthy Chinese subjects.

BACKGROUND: Fluticasone propionate is a synthetic trifluoro-substituted glucocorticoid, a highly sel...

ReIU: an efficient preliminary framework for Alzheimer patients based on multi-model data.

The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnos...

Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension.

OBJECTIVE: Congenital heart disease with pulmonary arterial hypertension (CHD-PAH), caused by CHD, i...

Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.

This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to m...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet...

Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.

BACKGROUND: Prior studies have demonstrated an association between retinal vascular features and car...

Type 2 diabetes prediction method based on dual-teacher knowledge distillation and feature enhancement.

Diabetes prediction is an important topic in the field of medical health. Accurate prediction can he...

Exercise improves body composition, physical fitness, and blood levels of C-peptide and IGF-1 in 11- to 12-year-old boys with obesity.

INTRODUCTION: Exercise is vital in preventing and treating obesity. Despite its importance, the unde...

Using Machine Learning to Predict Weight Gain in Adults: an Observational Analysis From the All of Us Research Program.

INTRODUCTION: Obesity, defined as a body mass index ≥30 kg/m, is a major public health concern in th...

Identification of Factors Influencing Donor-Derived Cell-Free DNA Levels up to One Year After Kidney Transplant.

Donor-derived cell-free DNA (dd-cfDNA) in the peripheral blood of allograft recipients has shown to...

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of c...

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