Diabetes

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this r...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermore, the computational cost of inspecting each pixel is expensive because the number of pixels is high even at low resolution. In this work, we propose...

Using Machine Learning to Construct the Blood-Follicle Distribution Models of Various Trace Elements and Explore the Transport-Related Pathways with Multiomics Data.

Permeabilities of various trace elements (TEs) through the blood-follicle barrier (BFB) play an important role in oocyte development. However, it has ...

A new intelligent system based deep learning to detect DME and AMD in OCT images.

Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular retinal diseases, playing a crucial role in diagn...

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with idiopathic membranous nephropathy (IMN) and recom...

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Multimodality fusion has gained significance in medical applications, particularly in diagnosing challenging diseases like eye diseases, notably diabe...

Appropriateness of Artificial Intelligence Chatbots and Diabetic Foot Ulcer Management: Comment.

UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for determining the status of obstruction, developing tr...

A multimodal approach using fundus images and text meta-data in a machine learning classifier with embeddings to predict years with self-reported diabetes - An exploratory analysis.

AIMS: Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new pa...

Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes.

AIM: To develop and employ machine learning (ML) algorithms to analyse electrocardiograms (ECGs) for the diagnosis of cardiac autonomic neuropathy (CA...

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.

Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualiz...

PROS1 is a crucial gene in the macrophage efferocytosis of diabetic foot ulcers: a concerted analytical approach through the prisms of computer analysis.

BACKGROUND: Diabetic foot ulcers (DFUs) pose a serious long-term threat because of elevated mortality and disability risks. Research on its biomarkers...

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

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 (...

Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence.

The rapid surge in artificial intelligence (AI) has dominated technological innovation in today's society. As experts begin to understand the potentia...

[Authors' reply to the letter to the editor "Artificial intelligence and screening for visual impairment related to diabetic retinopathy and macular edema"].

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. Artificial intelligence models (AIs) like Gemini (...

Advancements and turning point of artificial intelligence in ophthalmology: A comprehensive analysis of research trends and collaborative networks.

Artificial intelligence (AI) has emerged as a transformative force with great potential in various fields, including healthcare. In recent years, AI h...

Novel non-invasive method for urine mapping: Deep-learning-enabled SERS spectroscopy for the rapid differential detection of kidney allograft injury.

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual declin...

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

Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soari...

Attention-based deep learning framework for automatic fundus image processing to aid in diabetic retinopathy grading.

BACKGROUND AND OBJECTIVE: Early detection and grading of Diabetic Retinopathy (DR) is essential to determine an adequate treatment and prevent severe ...