Diabetes

Artificial intelligence in cancer survivorship: evaluating ChatGPT's performance in rehabilitation-related queries.

PURPOSE: This study aimed to evaluate the performance of ChatGPT in responding to patient-centered queries related to cancer rehabilitation. It examined the accuracy, completeness, and overall quality of ChatGPT's responses across major domains of cancer rehabilitation from a physical therapy perspective. METHODS: Fifteen representative patient queries covering eight domains of cancer rehabilitati...

Leveraging deep learning to infer continuous predictions from ordinal labels in medical imaging.

In clinical medicine, variables like disease severity are often categorized into discrete ordinal labels such as normal/mild/moderate/severe. However, these labels, commonly used to train and evaluate disease severity prediction models, simplify an underlying continuous severity spectrum. Using continuous scores can aid in detecting small severity changes more sensitively over time. We introduce a...

Targeted use of large language models for EHR-based computable phenotyping.

OBJECTIVE: Computable phenotypes derived from electronic health records (EHRs) are central to clinical research and quality reporting. Although large ...

Comparative assessment of diagnostic agreement between artificial intelligence and general practitioners in diabetic retinopathy screening using non-mydriatic fundus photography.

AIMS: To assess the diagnostic agreement between an artificial intelligence (AI) system and general practitioners (GPs) interpreting fundus photograph...

Unveiling varietal specificity in non-destructive grape quality monitoring: Explainable AI and feature selection for sugar and organic acid prediction using NIR spectroscopy.

Sugar and organic acid content are crucial factors determining grape quality. Non-destructive testing of these components aids in accurately determini...

Prospective Data Curation Enables High-Performance Artificial Intelligence for Diabetic Retinopathy Screening in a Resource-Limited Setting.

PURPOSE: To determine whether a high-quality, prospectively curated dataset can, by itself, enable the development of robust and clinically effective ...

The predictive value of serological markers for successful weaning and 30-day mortality in patients with severe intracerebral hemorrhage.

AIM: This study intends to screen serological indicators related to weaning outcomes and 30-day mortality in severe intracerebral hemorrhage (ICH) pat...

Current Controversies in Acromegaly Care.

Persistent disease after surgery for acromegaly is common. Expanding medical management options improves long-term biochemical and clinical outcomes, ...

Multimodal Machine Learning for Diabetic Peripheral Neuropathy Diagnosis: Methodological Advances and Future Directions.

Development and validation of an early risk prediction model based on inflammatory and metabolically derived markers for early diagnosis of diabetic kidney disease.

Thermo-Sensitive Polymeric Networks for Next-Generation Wound Management: A Review.

Wound healing is a dynamic and highly coordinated biological process involving hemostasis, inflammation, proliferation, and tissue remodeling. However...

Identification and Validation of Transcriptomic Signatures in Inflammatory Bowel Disease with Metabolic Syndrome via Bioinformatics and Machine Learning.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic, nonspecific inflammatory disorder affecting the gastrointestinal tract. The condition's pat...

Use of Continuous Glucose Monitoring With Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes.

The classification of diabetes and prediabetes by static glucose thresholds obscures the pathophysiological dysglycemia heterogeneity, primarily drive...

Fully Automatic Diabetic Wound Segmentation Using Lightweight Deep Convolutional Neural Networks.

Diabetic foot ulcers, resulting from neuropathic and/or vascular complications in patients with diabetes mellitus, pose a major global health challeng...

Gated Backbone Fusion with Transformer Encoder for Diabetic Foot Osteomyelitis Screening and Localization in Radiographs.

Diabetic foot osteomyelitis (DFO) is a leading cause of lower-extremity complications in individuals with diabetes, and timely, accurate screening is ...

Design of Single-Atom Nanozymes for Precision Treatment of Erectile Dysfunction with Integrated Single-Cell RNA Sequencing and Machine Learning.

Patients with diabetes mellitus-induced erectile dysfunction (DMED) usually suffer more severe symptoms, and efficacy of the first-line therapy is lim...

Accuracy of deep learning for risk prediction and screening of diabetic foot Ulcers: A systematic review and meta-analysis.

BACKGROUND: This research sought to systematically estimate the accuracy of deep learning (DL) in diagnosing diabetic foot ulcers (DFUs), thereby prov...

Accuracy of ChatGPT, Gemini, Claude and DeepSeek in Carbohydrate Counting.

AIMS: To evaluate the accuracy of four general-purpose artificial intelligence (AI) models-ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and D...

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characteri...

Diabetes Technology: An Update.

Diabetes is one of the most prevalent chronic diseases worldwide, with rates that continue to increase. Over 30 years ago, the Diabetes Control and Co...