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Related Concept Videos

Rheumatic Heart Disease III: Medical Management01:21

Rheumatic Heart Disease III: Medical Management

Rheumatic heart disease (RHD) management can be divided into two main strategies: prevention and long-term management.Primary PreventionPrimary prevention focuses on timely diagnosis and management of group A streptococcal pharyngitis to prevent acute rheumatic fever. The most widely used antibiotic for treating this condition is intramuscular benzathine penicillin G.Acute Rheumatic Fever TreatmentThe primary treatment goal for a patient diagnosed with acute rheumatic fever is to suppress the...
Rheumatic Heart Disease IV: Nursing Management01:20

Rheumatic Heart Disease IV: Nursing Management

AssessmentA comprehensive assessment is essential in managing a patient with rheumatic heart disease (RHD). Begin with obtaining a detailed medical history, including recent streptococcal infections, a history of rheumatic fever, or previously diagnosed rheumatic heart disease. Assess the patient for symptoms such as fever, chest pain, widespread joint pain (arthralgia), tachycardia, pericardial friction rub, muffled heart sounds, heart murmurs, peripheral edema, subcutaneous nodules, and...
Nephrotic Syndrome II : Assessment and Medical Management01:26

Nephrotic Syndrome II : Assessment and Medical Management

IntroductionNephrotic syndrome is a kidney disorder marked by excessive protein loss in the urine, leading to various systemic complications. This condition often results from damage to the glomeruli—the kidney's filtering units—causing proteinuria, low blood protein levels, and fluid retention. Understanding the assessment, diagnosis, and management of nephrotic syndrome is essential for effective treatment and prevention of further kidney damage.AssessmentPatient History: Document any history...
Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies01:22

Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies

The key clinical manifestations of Rheumatic heart disease (RHD) include several distinct cardiac symptoms.Carditis, a hallmark of acute rheumatic fever, involves inflammation of the heart's endocardium, myocardium, and pericardium. Chronic RHD often results from recurrent episodes of carditis. Its symptoms include the following:Murmurs are caused by valvular damage, especially to the mitral and aortic valves. Mitral stenosis or regurgitation is common, with characteristic heart murmurs...
Connective Tissue Cell Types01:22

Connective Tissue Cell Types

Connective tissue develops from the mesoderm of a developing embryo and consists of cells, fibers, and ground substance: a gel-like material containing large complexes of carbohydrates and proteins. Connective tissue was first identified as a separate tissue family in the 18th century, and Johannes Peter Muller coined the term connective tissue.
Fat cells (adipocytes), smooth muscle cells (myoblasts), and bone cells (osteoblasts) are some connective tissue cell types. Some immune system cells...
Nephrotic Syndrome III : Nursing Management01:24

Nephrotic Syndrome III : Nursing Management

Nursing management for nephrotic syndrome adapts as the disease progresses, with strategies evolving to address advancing symptoms and complications.Early-Stage Management In the early stages, nursing interventions for nephrotic syndrome resemble those used in managing acute glomerulonephritis, focusing on symptom monitoring, fluid balance, and managing mild to moderate edema.Vital Signs: Regularly monitor blood pressure, pulse, respiratory rate, and temperature to promptly identify...

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Related Experiment Video

Updated: May 24, 2026

Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain
04:50

Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain

Published on: May 16, 2025

Ontology-Enriched Guidelines Retrieval for Complex Rheumatological Cases.

Tommaso Mario Buonocore1,2, Sara Marino1, Giuseppe Albi1

  • 1Department of Computer, Electrical and Biomedical Engineering, University of Pavia, Pavia, Italy.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

Large language models (LLMs) with retrieval-augmented generation (RAG) aid clinical decisions. Integrating medical knowledge graphs significantly improves retrieval accuracy for complex medical queries.

Keywords:
Clinical Decision SupportGenerative AIKnowledge GraphsLarge Language ModelsRetrieval-Augmented GenerationRheumatic Diseases

Related Experiment Videos

Last Updated: May 24, 2026

Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain
04:50

Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain

Published on: May 16, 2025

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare

Background:

  • Large language models (LLMs) and retrieval-augmented generation (RAG) show promise for clinical decision support.
  • Current semantic retrieval methods struggle with the structured relationships inherent in complex medical knowledge.

Purpose of the Study:

  • To investigate the efficacy of ontology-based knowledge graphs for enhancing medical information retrieval.
  • To compare retrieval performance using embeddings-only, knowledge graph-only, and hybrid approaches.

Main Methods:

  • Developed a knowledge graph integrating SNOMED CT and rheumatology guidelines.
  • Evaluated retrieval performance on clinical queries using three configurations: embeddings-only, knowledge graph-only, and a hybrid model.

Main Results:

  • Embeddings-only retrieval was adequate for simple clinical queries.
  • Ontology-based knowledge graph retrieval demonstrated superior performance for complex reasoning tasks.
  • The hybrid approach showed potential but required further refinement.

Conclusions:

  • Ontology-based knowledge graphs are essential for improving the accuracy of LLM-based clinical decision support systems in complex medical scenarios.
  • Future work should focus on optimizing hybrid retrieval methods and expanding knowledge graph integration.