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Integrating education-based interventions and machine learning for stunting prevention: A case study in East Lombok, Indonesia.

One of the regions in Indonesia that has the highest prevalence of stunting cases is West Nusa Tenggara, with a percentage of cases almost reaching 12.7 %, even though this province is a priority target for stunting reduction by 2022. Specifically in the East Lombok region, this study took this location point because of the high number of stunting cases in West Nusa Tenggara. Puskesmas Denggen was...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, psoriatic arthritis, and systemic lupus erythematosus, report moderate to severe pain despite controlled inflammation, driving interest in self-management including use of cannabis. We applied natural language processing (NLP) to 2.6 million electronic health record notes from 5051 adults with ARDs see...

Precision engineering of anti-atherosclerotic herbal nanomedicine: from machine learning-aided active components screening to optimized metal-phenolic network codelivery.

Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditiona...

A machine learning-based assessment strategy for Artemisia argyi Folium: Exploring the dose-effect relationship between anti-inflammatory activity and chemical composition.

ETHNOPHARMACOLOGICAL RELEVANCE: Artemisia argyi Folium (AAF) has been traditionally used for its medicinal properties, and understanding its anti-infl...

Predicting Pharmacological Treatment Response in Migraine Using AI/ML: A Scoping Review of the Evidence and Future Directions.

The treatment of migraine is hampered by inter-individual variability, leading to an inefficient "trial and error" approach. Artificial intelligence (...

Identification of the core genes KLRB1 and RETN as potential shared diagnostic markers for major depressive disorder and systemic lupus erythematosus through bioinformatics and machine learning methodologies.

This study investigates the shared molecular mechanisms between major depressive disorder (MDD) and systemic lupus erythematosus (SLE) through integra...

Effective alternative strategies to combat challenges associated with MDR bacterial infections: Drug repurposing, role of artificial intelligence, and novel therapeutic options.

Antibiotic failure has emerged as a critical global health concern, driven by a combination of factors including the stagnation in the discovery of ne...

Ligand-based prediction of anti-bacterial compounds: Overcoming class imbalance in molecular data.

In the emergence of pan-drug-resistant bacteria, there is an urgent demand for the discovery of structurally novel antibiotics. While traditional drug...

Iterative learning for joint image denoising and motion artifact correction of 3D brain MRI.

Image noise and motion artifacts greatly affect the quality of brain magnetic resonance imaging (MRI) and negatively influence downstream medical imag...

Design and optimization of indomethacin-loaded solid dispersion orally dissolving films: Machine learning and molecular dynamics study.

Indomethacin (IND) is a nonsteroidal anti-inflammatory drug (NSAID) with anti-inflammatory, analgesic, and antipyretic properties, and is widely used ...

Simulation-guided optimization of one-step gold nanoparticle amplification for paper-based detection of anti-IFN-γ autoantibodies.

Adult-onset immunodeficiency (AOID) caused by anti-interferon-γ autoantibodies (anti-IFN-γ Abs) lacks rapid, sensitive diagnostic tools suitable for f...

Graph-Contrastive Convolutional Neural Network for Extracting and Classifying Peptide-Based Periodontal Immunomodulatory and Anti-Inflammatory Signatures.

INTRODUCTION: Periodontitis is a chronic inflammatory disease that occurs when the body's immune system fails to respond properly to microbial biofilm...

Multi-omics and machine learning framework reveals ABCG2 as a therapeutic target of Eleven Flavored Shenqi Tablets in clear cell renal cell carcinoma.

ETHNOPHARMACOLOGICAL RELEVANCE: Eleven Flavored Shenqi Tablets (EFST) is a classical multi-herbal prescription in traditional Chinese medicine, tradit...

Optimized ensemble learning with multi-feature fusion for enhanced anti-inflammatory peptide prediction.

Anti-inflammatory peptides (AIPs) represent promising therapeutic agents, however, their discovery via traditional experimental methods is constrained...

Extraction, preparation, pharmacological activities, and potential applications of ginsenosides Rk1 and Rg5.

ETHNOPHARMACOLOGICAL RELEVANCE: Panax species (Panax ginseng, Panax quinquefolius L., and Panax notoginseng) are globally recognized as valuable medic...

Artificial intelligence in age-related macular degeneration: Advancing diagnosis, prognosis, and treatment.

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults. While anti-vascular endothelial growth factor (...

Nivolumab plus ipilimumab for potentially resectable hepatocellular carcinoma: Long-term efficacy and biomarker exploration.

BACKGROUND & AIMS: Immune checkpoint inhibitor-based combination therapy has demonstrated high objective response rates in patients with hepatocellula...

Comparison of ChatGPT-3.5, ChatGPT-4.0 and DeepSeek in generating dietary plans for patients with chronic kidney disease: A focus on nutritional accuracy and dietary inflammation.

BACKGROUND: Our previous research indicated that ChatGPT-3.5 was inadequate in generating nutritionally accurate dietary plans for patients with chron...

Elucidating anti-triple-negative breast cancer mechanisms and mitigating toxicity of Fritillaria thunbergii Miq.: A multi-omics and network pharmacology approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria thunbergii Miq. (Zhebeimu, ZBM) is traditionally recognized in Chinese medicine for its effects of clearin...

Effectiveness of artificial intelligence in classification of connective tissue diseases in patients with anti-nuclear antibody (ANA) positivity.

OBJECTIVES: The study aimed to investigate the classification performance of artificial intelligence (AI) in diagnosing connective tissue diseases(CTD...