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

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

5.2K
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...
5.2K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

126
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
126
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
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...
5.9K
Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

1.1K
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Prognostic value of HRCT-based risk stratification for acute/subacute progression in polymyositis/dermatomyositis-associated interstitial lung disease.

Frontiers in immunology·2026
Same author

Prognostic value of lesion-specific and proximal coronary segment pericoronary adipose tissue CT Attenuation in ischemic heart disease with angina pectoris.

Scientific reports·2025
Same author

Radiomics analysis of pericoronary adipose tissue for detecting ischaemia with non-obstructive coronary arteries in NAFLD patients.

BMC cardiovascular disorders·2025
Same author

Spin Liquid and Superconductivity Emerging from Steady States and Measurements.

Physical review letters·2025
Same author

The Impact of Linguistic Signals on Cognitive Change in Support Seekers in Online Mental Health Communities: Text Analysis and Empirical Study.

Journal of medical Internet research·2025
Same author

Higher-Form Symmetries under Weak Measurement.

Physical review letters·2024

Related Experiment Video

Updated: Oct 18, 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

755

A Personalized Medical Decision Support System Based on Explainable Machine Learning Algorithms and ECC Features:

Dongxiao Gu1,2, Wang Zhao1,2, Yi Xie1,2

  • 1The School of Management, Hefei University of Technology, Hefei 230009, China.

Diagnostics (Basel, Switzerland)
|September 28, 2021
PubMed
Summary
This summary is machine-generated.

This study enhances artificial intelligence for breast cancer diagnosis by incorporating external case characteristics (ECC) into personalized medical decision support systems (PMDSS-BCAD). This approach improves diagnostic accuracy and physician trust, promoting AI adoption in clinical settings.

Keywords:
case-based reasoningexternal features of casesmachine learningpersonalized recommendationsphysician adoption

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.3K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.4K

Related Experiment Videos

Last Updated: Oct 18, 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

755
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.3K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.4K

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Medicine
  • Oncology

Background:

  • Artificial intelligence (AI) offers potential to improve breast cancer diagnosis accuracy.
  • Physician adoption of AI recommendations is crucial for effectiveness but often limited.
  • Personalized medical decision support systems (PMDSS) require refinement to enhance trust and utility.

Purpose of the Study:

  • To investigate the impact of external case characteristics (ECC) on the accuracy of AI-driven personalized medical decision support systems for breast cancer assisted diagnosis (PMDSS-BCAD).
  • To develop and evaluate a novel case-based reasoning (CBR) framework that integrates ECC into AI diagnostic models.
  • To enhance physician trust and adoption of AI-generated diagnostic recommendations.

Main Methods:

  • Developed a comprehensive case-based reasoning (CBR) framework incorporating external case characteristics (CBR-ECC).
  • Utilized Naive Bayes and k-nearest neighbor (KNN) algorithms within the CBR-ECC framework.
  • Integrated the CBR-ECC model and external features into a PMDSS-BCAD system for evaluation.

Main Results:

  • The combined Naive Bayes and KNN model achieved a diagnostic accuracy of 99.40% under the new CBR framework.
  • The PMDSS-BCAD system, incorporating ECC, was rated superior to the original system by users in a hospital setting.
  • External case characteristics significantly improved the effectiveness and user acceptance of the AI system.

Conclusions:

  • The developed PMDSS-BCAD system provides more personalized and accurate auxiliary diagnostic results for breast cancer.
  • Integrating external case characteristics enhances physician trust in AI recommendations, encouraging greater adoption.
  • This approach represents a significant advancement in AI-assisted medical diagnosis, particularly for complex diseases like breast cancer.