Primary Care

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

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Developing probabilistic ensemble machine learning models for home-based sleep apnea screening using overnight SpO2 data at varying data granularity.

PURPOSE: This study aims to develop sleep apnea screening models with overnight SpO2 data, and to in...

Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model.

Obstructive sleep apnea syndrome disrupts sleep, destroys the homeostasis of biological systems such...

Identification and evaluation of deep foundation pit construction risks based on Grey-DEMATEL-Fuzzy comprehensive evaluation method.

In recent years, foundation pit construction has been rapidly developing in the direction of deep an...

Enhanced machine learning approaches for OSA patient screening: model development and validation study.

Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors f...

Artificial Intelligence and Cardiology Practice in Nigeria: Are We Ready?

Cardiovascular diseases are the leading cause of death globally. As cardiovascular risk factors cont...

Machine learning assessment of vildagliptin and linagliptin effectiveness in type 2 diabetes: Predictors of glycemic control.

OBJECTIVE: Differential effects of linagliptin and vildagliptin may help us personalize treatment fo...

The AI revolution in glaucoma: Bridging challenges with opportunities.

Recent advancements in artificial intelligence (AI) herald transformative potentials for reshaping g...

Development and Testing of Artificial Intelligence-Based Mobile Application to Achieve Cataract Backlog-Free Status in Uttar Pradesh, India.

BACKGROUND: Uttar Pradesh (UP), the most populous state in India, has about 36 million people aged 5...

Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic comp...

Venous thromboembolism in the era of machine learning and artificial intelligence in medicine.

In this review, we embark on a comprehensive exploration of venous thromboembolism (VTE) in the cont...

Enhancing cervical cancer cytology screening via artificial intelligence innovation.

A double-check process helps prevent errors and ensures quality control. However, it may lead to dec...

Neural network analysis of pharyngeal sounds can detect obstructive upper respiratory disease in brachycephalic dogs.

Brachycephalic obstructive airway syndrome (BOAS) is a highly prevalent respiratory disease affectin...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

The kidney is an abdominal organ in the human body that supports filtering excess water and waste fr...

Machine learning surveillance of foodborne infectious diseases using wastewater microbiome, crowdsourced, and environmental data.

Clostridium perfringens (CP) is a common cause of foodborne infection, leading to significant human ...

Machine learning-based reproducible prediction of type 2 diabetes subtypes.

AIMS/HYPOTHESIS: Clustering-based subclassification of type 2 diabetes, which reflects pathophysiolo...

DECNet: Left Atrial Pulmonary Vein Class Imbalance Classification Network.

In clinical practice, the anatomical classification of pulmonary veins plays a crucial role in the p...

Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.

BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship b...

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