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Related Concept Videos

Serum Laboratory Studies, Stool Test, Breath Test01:30

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Gastrointestinal (GI) diagnostic studies are pivotal in confirming, ruling out, diagnosing, or staging various diseases, including cancers. Following diagnosis, allocating time for discussions with the patient and providing informational resources is crucial. Diagnostic assessments of the GI tract often occur in outpatient settings like endoscopy suites or GI labs. Preparation for these tests may include dietary restrictions, fasting, liquid bowel preparations, laxatives, enemas, and the...
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Related Experiment Video

Updated: Jun 26, 2025

Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro
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Intelligent Liver Function Testing (iLFT): An Intelligent Laboratory Approach to Identifying Chronic Liver Disease.

Jennifer Nobes1,2, Damien Leith3,4, Sava Handjiev1,4

  • 1Department of Blood Sciences, NHS Tayside, Ninewells Hospital, Dundee DD1 9SY, UK.

Diagnostics (Basel, Switzerland)
|May 11, 2024
PubMed
Summary
This summary is machine-generated.

The intelligent Liver Function Testing (iLFT) pathway streamlines abnormal liver function test (LFT) investigations in primary care. This automated system provides crucial feedback, improving patient care and reducing chronic liver disease mortality.

Keywords:
algorithmautomationchronic liver diseasediagnosisfibrosisintelligentlaboratoryliver function testsmanagementprecision medicinereferral

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Area of Science:

  • Clinical chemistry
  • Health informatics
  • Diagnostic algorithms

Background:

  • Rising chronic liver disease mortality and numerous uninvestigated abnormal liver function tests (LFTs) necessitated a new approach.
  • Existing LFT investigation pathways were often inefficient and lacked automated clinical feedback.

Purpose of the Study:

  • To outline the development and implementation of the intelligent Liver Function Testing (iLFT) pathway.
  • To evaluate the utility, outcomes, and evolution of the iLFT system.
  • To explore future applications of intelligent systems in laboratory diagnostics.

Main Methods:

  • Development of an algorithm-based system for automated laboratory investigations.
  • Integration of clinical feedback for abnormal LFT results.
  • Implementation within primary care settings.

Main Results:

  • The iLFT pathway was utilized over 11,000 times in its first three years.
  • Demonstrated implications for diagnostic laboratories, primary care, and specialist hepatology clinics.
  • Provided a framework for improved LFT investigation and management.

Conclusions:

  • The iLFT pathway offers a valuable, automated solution for managing abnormal LFTs.
  • Intelligent systems have the potential to enhance laboratory investigation value.
  • Further adoption of similar approaches could improve patient outcomes in liver disease management.