Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Integrated Healthcare System01:20

Integrated Healthcare System

An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Optimisation and comparative extraction of safranal from <i>Crocus sativus</i> L. stigmas and commercial saffron products using response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS).

Natural product researchยท2026
Same author

Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

PloS oneยท2021
Same author

A New Intelligent Medical Decision Support System Based on Enhanced Hierarchical Clustering and Random Decision Forest for the Classification of Alcoholic Liver Damage, Primary Hepatoma, Liver Cirrhosis, and Cholelithiasis.

Journal of healthcare engineeringยท2018
Same author

A Novel Hybrid Feature Selection Model for Classification of Neuromuscular Dystrophies Using Bhattacharyya Coefficient, Genetic Algorithm and Radial Basis Functionย Based Support Vector Machine.

Interdisciplinary sciences, computational life sciencesยท2016
Same author

Threat driven modeling framework using petri nets for e-learning system.

SpringerPlusยท2016
Same author

Calcium and magnesium levels during automated plateletpheresis in normal donors.

Transfusion medicine (Oxford, England)ยท2005
Same journal

sEEGnal: an automated EEG preprocessing pipeline evaluated against expert-driven preprocessing.

Computers in biology and medicineยท2026
Same journal

Corrigendum to "Integrating experimental biology, computational methods, and artificial Intelligence in anticancer drug discovery: Bridging the translational Gap" [Comput. Biol. Med. 213 (2026) 111832].

Computers in biology and medicineยท2026
Same journal

Organ dose optimization for a point-of-care forearm X-ray photon-counting CT.

Computers in biology and medicineยท2026
Same journal

Physics-guided transformation of breathomic feature spaces into disease-specific representations for respiratory disease classification.

Computers in biology and medicineยท2026
Same journal

An AI-driven deep learning pipeline for taxonomic classification and biodiversity assessment of deep-sea environmental DNA.

Computers in biology and medicineยท2026
Same journal

Rapid personalisation of cardiovascular models using invasively measured right ventricular pressure.

Computers in biology and medicineยท2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Knowledge and intelligent computing system in medicine.

Babita Pandey1, R B Mishra

  • 1Department of Computer Engineering, Information Technology, BHU, UP 221005, India. shukla_babita@yahoo.co.in

Computers in Biology and Medicine
|February 10, 2009
PubMed
Summary
This summary is machine-generated.

This study reviews 185 singular and combined methods in medical expert systems, including knowledge-based systems (KBS) and intelligent computing methods (ICM), from 1970-2008. Most methods are applied to medical diagnosis, with fewer used for planning and treatment.

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Jun 25, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Artificial Intelligence in Medicine
  • Medical Informatics
  • Computational Intelligence

Background:

  • Knowledge-based systems (KBS) and intelligent computing methods (ICM) are integral to medical planning, diagnosis, and treatment.
  • KBS includes rule-based reasoning (RBR), case-based reasoning (CBR), and model-based reasoning (MBR).
  • ICM encompasses genetic algorithms (GA), artificial neural networks (ANN), and fuzzy logic (FL).

Purpose of the Study:

  • To comprehensively review singular and combined AI methods applied in the medical domain from the mid-1970s to 2008.
  • To categorize and present the features, processes, and applications of these methods.
  • To provide a resource for researchers new to medical expert systems.

Main Methods:

  • Systematic review and tabulation of 185 distinct and hybrid AI methods.
  • Classification of methods based on their components (KBS, ICM, or combined).
  • Analysis of application areas: diagnosis, treatment, and planning.

Main Results:

  • The study identified and analyzed 185 singular and combined methods.
  • Methods were categorized and their medical applications detailed in tabular form.
  • A significant majority of methods were found to be applied in medical diagnosis, with moderate application in treatment and limited use in planning.

Conclusions:

  • The review highlights the prevalence of AI methods in medical diagnosis.
  • There is a need for further development and application of AI in medical planning and treatment.
  • This comprehensive study serves as a valuable guide for novice researchers in medical expert systems.