Primary Care

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

16,291 articles
Stay Ahead - Weekly Primary Care research updates
Subscribe
Browse Categories
Showing 3193-3213 of 16,291 articles
A Machine Learning Approach for Predicting Early Phase Postoperative Hypertension in Patients Undergoing Carotid Endarterectomy.

BACKGROUND: This study aimed to establish and validate a machine learning-based model for the predic...

A deep learning approach based on convolutional LSTM for detecting diabetes.

Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or ...

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.

Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 dia...

Identifying Fatal Head Injuries on Postmortem Computed Tomography Using Convolutional Neural Network/Deep Learning: A Feasibility Study.

Postmortem computed tomography (PMCT) is a relatively recent advancement in forensic pathology pract...

Probing the characteristics and biofunctional effects of disease-affected cells and drug response via machine learning applications.

Drug-induced transformations in disease characteristics at the cellular and molecular level offers t...

Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study.

The last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledge...

Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning.

BACKGROUND: Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to ...

Stability assessment of extracts obtained from Arbutus unedo L. fruits in powder and solution systems using machine-learning methodologies.

Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially...

Predicting Binding from Screening Assays with Transformer Network Embeddings.

Cheminformatics aims to assist in chemistry applications that depend on molecular interactions, stru...

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes...

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, ...

Near-optimal insulin treatment for diabetes patients: A machine learning approach.

Blood glycemic control is crucial for minimizing severe side effects in diabetes mellitus. Currently...

Finding undiagnosed patients with hepatitis C infection: an application of artificial intelligence to patient claims data.

Hepatitis C virus (HCV) remains a significant public health challenge with approximately half of the...

Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques.

Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection...

Truncated inception net: COVID-19 outbreak screening using chest X-rays.

Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a ...

Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation.

In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue ...

Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

BACKGROUND: The clinical utility of machine-learning (ML) algorithms for breast cancer risk predicti...

Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists.

Since the last decade, most of our daily activities have become digital. Digital health takes into a...

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health ...

Browse Categories