Primary Care

Deep Learning-Enhanced Generation and Screening of Antihyperuricemic Peptides from Chickpea Proteins: from Multienzyme Optimization to Molecular Mechanisms.

Food-derived bioactive peptides have emerged as promising functional ingredients for hyperuricemia management. However, multienzyme hydrolysis strategies remain underexplored because of inefficient screening methods. Herein, a large language model (LLM)-guided strategy integrating deep learning-assisted enzyme selection with experimental validation was developed to generate antihyperuricemic pepti...

Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study.

PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typically relies on dental examinations and radiographs, which may be underutilised by individuals who avoid, delay, or lack dental care. This study evaluated the potential of routine blood biomarkers and demographic data for screening moderate-to-severe per...

Using a large language model as a third reviewer to augment dual human full-text screening in orthopaedic systematic reviews.

PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that have emerged as potential tools to augment systematic review wor...

Integrating machine learning models to map springshed potential zones using key environmental variables in high-altitude Himalayan terrain.

This study presents an integrated machine learning framework to predict potential spring occurrence zones in the high-altitude Kishtwar region of the ...

Predictive performance of CT-based artificial intelligence for predicting variceal bleeding in portal hypertension: a systematic review and meta-analysis.

OBJECTIVES: To systematically evaluate the predictive accuracy of computed tomography (CT)-based artificial intelligence (AI) for predicting variceal ...

Extracting Signs and Symptoms of Hypertensive Disorders in Pregnancy from Clinical Notes Using Natural Language Processing.

PURPOSE: Hypertensive disorders in pregnancy (HDP) affect 16% of births in the United States. In this pilot study, we conducted a preliminary evaluati...

A long-term image-derived AI-based risk model for primary prevention of breast cancer in individuals at high risk.

Image-derived artificial intelligence (AI) risk models have shown promise in short-term risk assessment for improving breast cancer (BC) screening. No...

Comparing Stakeholders' Perspectives on Parkinson Disease Management and Digital Technologies: Exploratory International Survey.

BACKGROUND: Parkinson disease (PD) is a progressive neurodegenerative disorder that poses complex challenges for persons with PD, informal caregivers,...

Alignment Between Cardiologists and AI-Driven Diagnostic Systems: Mixed Methods Study.

BACKGROUND: The clinical value of artificial intelligence (AI)-based diagnostic systems depends not only on their accuracy but also on how well their ...

Predicting Treatment Failure With Sodium-Glucose Cotransporter-2 Inhibitors in People With Type 2 Diabetes: Novel Artificial Intelligence and Machine Learning Approach.

BACKGROUND: The rate of treatment failure with sodium-glucose cotransporter-2 inhibitors (SGLT2i) is high among individuals with type 2 diabetes (T2D)...

Patient preferences and willingness-to-pay for AI-enabled blended type 2 diabetes care by digital experience and socioeconomic status: a discrete-choice experiment in China.

OBJECTIVES: To elicit stated preferences and willingness-to-pay (WTP) for artificial intelligence (AI)-enabled blended care in type 2 diabetes mellitu...

A deep-learning framework reveals whole-body perturbations at cell level.

Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2. However, tools for comprehensive, ...

National trends and comparative outcomes of insulin versus non-insulin therapy in acute ischemic stroke patients treated with mechanical thrombectomy: a retrospective cohort study using the national inpatient sample.

Background diabetes mellitus is prevalent among patients with acute ischemic stroke (AIS). The prognostic significance of long-term insulin treatment ...

Development of colorimetric and machine learning based accurate glucose detection platform for point of care applications.

Improving overall health and preventing complications is crucial for timely and effective treatment of diabetes patients. In this direction, accurate ...

Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.

BACKGROUND: Accurate and timely disease detection is essential in modern healthcare. Conventional imaging methods such as computed tomography (CT), ma...

Application of Health Examination in Early Screening of Tumors.

Early detection of tumors constitutes a cornerstone of cancer prevention and control. Medical assessments alongside emerging screening modalities prov...

Prospects and Challenges of Personalized Immunotherapy in Breast Cancer Treatment and Long-term Cancer Management.

Breast cancer is highly heterogeneous,and different molecular subtypes exhibit significant variations in their response to immunotherapy.While signifi...

PyRMD Studio: A Unified Suite for Next-Generation, AI-Powered Virtual Screening.

Artificial Intelligence (AI) has become a cornerstone of modern drug discovery. Yet, its widespread adoption is often hindered by the steep learning c...

Biological and Social Risk Factors for Predicting Type 2 Diabetes in Youth with Prediabetes: Review of Existing Prediction Models.

With the rising prevalence of type 2 diabetes (T2D) among children and adolescents, the ability to predict the progression of prediabetes to T2D in yo...

Machine learning and dose response effect models: an integrated approach to analyze the association between environmental variables and Cuneo Emergency Department admissions for Acute Otitis Media (2007-2015).

Acute otitis media (AOM) is a leading cause of pediatric Emergency Department visits, particularly among children under five years of age. Although it...