AI Medical Compendium Topic

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Blood Glucose

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Physical Activity Detection for Diabetes Mellitus Patients Using Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Diabetes mellitus (DM) is a persistent metabolic disorder associated with the hormone insulin. The two main types of DM are type 1 (T1DM) and type 2 (T2DM). Physical activity plays a crucial role in the therapy of diabetes, benefiting both types of p...

Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review.

Artificial intelligence in medicine
Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soaring costs of insulin present significant challenges to ensuring affordable management. This paper con...

Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge.

IEEE transactions on biomedical circuits and systems
Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However,...

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

Scientific reports
We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learning algorithms. The artificial intelligence prediction models were built in Python, primarily using ar...

Development of Machine Learning Models for the Identification of Elevated Ketone Bodies During Hyperglycemia in Patients with Type 1 Diabetes.

Diabetes technology & therapeutics
Diabetic ketoacidosis (DKA) is a serious life-threatening condition caused by a lack of insulin, which leads to elevated plasma glucose and metabolic acidosis. Early identification of developing DKA is important to start treatment and minimize compl...

The Development and Potential Applications of an Automated Method for Detecting and Classifying Continuous Glucose Monitoring Patterns.

Journal of diabetes science and technology
INTRODUCTION: Continuous glucose monitoring (CGM) is emerging as a transformative tool for helping people with diabetes self-manage their glucose and supporting clinicians in effective treatment. Unfortunately, many CGM users, and clinicians, find in...

Machine Learning Method and Hyperspectral Imaging for Precise Determination of Glucose and Silicon Levels.

Sensors (Basel, Switzerland)
This article introduces an algorithm for detecting glucose and silicon levels in solution. The research focuses on addressing the critical need for accurate and efficient glucose monitoring, particularly in the context of diabetic management. Underst...

Improved Glycemic Control through Robot-Assisted Remote Interview for Outpatients with Type 2 Diabetes: A Pilot Study.

Medicina (Kaunas, Lithuania)
: Our research group developed a robot-assisted diabetes self-management monitoring system to support Certified Diabetes Care and Education Specialists (CDCESs) in tracking the health status of patients with type 2 diabetes (T2D). This study aimed to...

DiaNet v2 deep learning based method for diabetes diagnosis using retinal images.

Scientific reports
Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases remaining undiagnosed, particularly in the Middle East North Africa (MENA) region, more accurate and acc...

Can adverse childhood experiences predict chronic health conditions? Development of trauma-informed, explainable machine learning models.

Frontiers in public health
INTRODUCTION: Decades of research have established the association between adverse childhood experiences (ACEs) and adult onset of chronic diseases, influenced by health behaviors and social determinants of health (SDoH). Machine Learning (ML) is a p...