Primary Care

Role of artificial intelligence in critical care nutrition support and research.

Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal nutrition strategy, however, remains a subject of intense debate. Artificial intelligence (AI) applications are becoming increasingly common in medicine, and specifically in critical care, driven by the data-rich environment of intensive care units. In this review, we will examine the evidence rega...

An artificial intelligence platform for the screening and managing of strabismus.

OBJECTIVES: Considering the escalating incidence of strabismus and its consequential jeopardy to binocular vision, there is an imperative demand for expeditious and precise screening methods. This study was to develop an artificial intelligence (AI) platform in the form of an applet that facilitates the screening and management of strabismus on any mobile device.

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein t...

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbiditi...

Artificial intelligence chatbots for the nutrition management of diabetes and the metabolic syndrome.

BACKGROUND: Recently, there has been a growing interest in exploring AI-driven chatbots, such as ChatGPT, as a resource for disease management and edu...

Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence.

As an integral aspect of health care, digital technology has enabled modelling of complex relationships to detect, screen, diagnose, and predict patie...

Assessing the article screening efficiency of artificial intelligence for Systematic Reviews.

OBJECTIVES: Artificial intelligence (AI) tools utilizing machine learning (ML) have gained increasing utility in medicine and academia as a means of e...

Advancements in AI based healthcare techniques with FOCUS ON diagnostic techniques.

Since the past decade, the interest towards more precise and efficient healthcare techniques with special emphasis on diagnostic techniques has increa...

Artificial intelligence meets pulmonary hypertension: early detection for a late-presenting disease.

Implementation of Digital Pathology and Artificial Intelligence in Routine Pathology Practice.

The advent of affordable technology has significantly influenced the practice of digital pathology, leading to its growing adoption within the patholo...

Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms.

INTRODUCTION: In 2021, the International Diabetes Federation reported that 537 million people worldwide are living with diabetes. While glucagon-like ...

Explainable deep recurrent neural networks for the batch analysis of a pharmaceutical tableting process in the spirit of Pharma 4.0.

Due to the continuously increasing Cost of Goods Sold, the pharmaceutical industry has faced several challenges, and the Right First-Time principle wi...

Detection of atrial fibrillation using a nonlinear Lorenz Scattergram and deep learning in primary care.

BACKGROUND: Atrial fibrillation (AF) is highly correlated with heart failure, stroke and death. Screening increases AF detection and facilitates the e...

Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care phys...

Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method.

BACKGROUND: Cognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of...

Smoking Classification Using Novel Plasma Cytokines by implementing Machine Learning and Statistical Methods.

Smoking is a major cause of premature and preventable death. Tobacco exposure has a detrimental effect on many organs and contributes to multiple dise...

Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs.

BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensem...

Brief Review and Primer of Key Terminology for Artificial Intelligence and Machine Learning in Hypertension.

Recent breakthroughs in artificial intelligence (AI) have caught the attention of many fields, including health care. The vision for AI is that a comp...

Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report.

Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (A...

Automatic classification and grading of canine tracheal collapse on thoracic radiographs by using deep learning.

Tracheal collapse is a chronic and progressively worsening disease; the severity of clinical symptoms experienced by affected individuals depends on t...