Primary Care

Commercialization path of data-driven green catalytic technology: the application of machine learning in technology lifecycle management.

In the context of the global strategy of sustainable development and carbon neutrality, green catalytic technology, as the core of achieving efficient and clean chemical conversion, has a complex and uncertain path from laboratory innovation to large-scale commercial application. The traditional R&D and commercialization models are often limited by bottlenecks such as high trial and error costs, l...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretinal screening of patients with diabetes. DESIGN: Cross-sectional study of retinal images. SUBJECTS: Ten thousand, five hundred thirty eye images from 2939 patients with diabetes who underwent teleretinal screening at the University of California clini...

The Burden of Delayed Diabetic Retinopathy Management and Use of Artificial Intelligence-Driven Screening Tools: A Systematic Literature Review.

PURPOSE: Patients with diabetic retinopathy (DR) are at risk of visual deterioration owing to systemic and financial barriers in accessing appropriate...

Explainable machine learning for depression risk prediction in adults with obesity: development of an online tool.

Screening for Tumor Microtube-Targeting Drugs Identifies PKC Modulators as Multipotent Inhibitors of Glioblastoma Progression.

UNLABELLED: Glioblastomas are incurable primary brain tumors that depend on neural-like cellular processes, tumor microtubes (TM), to invade the brain...

Seasonal variation in BMI outcomes at 6 months: secondary analyses of a multidisciplinary healthy lifestyle programme for children and adolescents with obesity.

BACKGROUND: While international evidence suggests seasonal variations may influence outcomes of interventions for pediatric obesity, data for Aotearoa...

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing ...

Combating Antiviral Drug Resistance: A Multipronged Strategy.

ConspectusViral proteases are essential enzymes required for viral replication and assembly, making them prime antiviral drug targets. However, under ...

Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models.

BACKGROUND: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although...

Real-world performance of an AI system for diabetic retinopathy screening.

Diabetic retinopathy (DR) is a leading cause of preventable blindness, and the growing global burden of diabetes is placing increasing pressure on oph...

Development of deep learning model to screen for primary open-angle glaucoma in African ancestry individuals.

Primary open-angle glaucoma (POAG) screening using artificial intelligence (AI) has emerged as a transformative method to identify undiagnosed disease...

Emerging trends in the early diagnosis of dental caries: a scoping review of artificial intelligence, digital diagnostics, and teledentistry.

BACKGROUND: Dental caries is the most prevalent chronic, noncommunicable condition affecting individuals of all ages and socio-economic status. The re...

Comparison of the predictive power of novel insulin resistance, lipid metabolism and obesity indices for the risk of developing dyslipidaemia in adults.

Artificial-intelligence-enabled digital stethoscope improves point-of-care screening for moderate-to-severe valvular heart disease.

AIMS: Valvular heart disease (VHD) can affect more than one in two adults over 65 yet remains underdiagnosed due to the limitations of traditional aus...

Mechanism of action of piperine in the treatment of retinal ischemic injury based on bioinformatics and network pharmacology.

Piperine is a common anti-ischemic compound and an active ingredient of herbal medicine for various ailments. It is widely sourced and affordable. How...

Salivary extracellular vesicles and Raman spectroscopy in precision diagnostics of type 2 diabetes.

Type 2 Diabetes (T2D) remains a major global health issue, driven by sedentary lifestyles and aging populations, emphasizing the urgent need for preci...

Coupling Data-Driven and Reinforcement Learning for Material Development and Device Management in Batteries.

The growing demand for high-energy, safe, and durable batteries demands innovative strategies in both material discovery and device management. Conven...

A Multimodal Model for Caries Screening Using Intraoral Images and Questionnaires.

INTRODUCTION AND AIMS: To develop a multimodal deep learning model for dental caries screening in children by integrating intraoral photographs and qu...

Developing an Interpretable Machine Learning Framework to Predict and Analyse Early Childhood Caries in Children Aged 2 to 6 Years: A Single-centre Observational Study.

BACKGROUND: Early childhood caries (ECC) is a prevalent global oral health condition, exerting profound adverse effects on children's oral health, gen...

Wearable electrochemical biosensors for non-invasive sport doping control: sweat and saliva as dual biofluid platforms.

The integrity of competitive athletics is increasingly compromised by sophisticated pharmacologies, rendering traditional sporadic testing of urine an...