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 Experiment Videos

Constraint reasoning in deep biomedical models.

Jorge Cruz1, Pedro Barahona

  • 1Departamento de Informática, Centro de Inteligência Artificial, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal. jc@di.fct.unl.pt

Artificial Intelligence in Medicine
|May 12, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

IPOscore: An interactive web-based platform for postoperative surgical complications analysis and prediction in the oncology domain.

Computer methods and programs in biomedicine·2022
Same author

KiMoSys 2.0: an upgraded database for submitting, storing and accessing experimental data for kinetic modeling.

Database : the journal of biological databases and curation·2020
Same author

Uniportal VATS Lobectomy: Subxiphoid Approach.

Revista portuguesa de cirurgia cardio-toracica e vascular : orgao oficial da Sociedade Portuguesa de Cirurgia Cardio-Toracica e Vascular·2018
Same author

Extended thymectomy, left pneumonectomy, pericardiectomy and partial pleurectomy for a large thymoma, using only a median sternotomy.

International journal of surgery case reports·2017
Same author

The tipping point: When should a modification become the standard technique?

The Journal of thoracic and cardiovascular surgery·2016
Same author

A simple modification to lower incidence of heart block with sutureless valve implantation.

The Journal of thoracic and cardiovascular surgery·2016
Same journal

Real-time EEG-based epileptic seizure prediction using artificial intelligence: A systematic review.

Artificial intelligence in medicine·2026
Same journal

R-peak detection and ECG data compression scheme based on empirical mode decomposition and wavelet transform.

Artificial intelligence in medicine·2026
Same journal

CastNet: A three-channel EEG-based deep learning model for cross-subject depression detection.

Artificial intelligence in medicine·2026
Same journal

State-of-the-art TinyML approaches for colorectal cancer detection: Current advances, challenges, and future directions.

Artificial intelligence in medicine·2026
Same journal

JRadiEvo: A Japanese radiology report generation model enhanced by evolutionary optimization of model merging.

Artificial intelligence in medicine·2026
Same journal

Causally-informed deep learning towards explainable and generalizable outcome prediction in critical care.

Artificial intelligence in medicine·2026
See all related articles

Constraint reasoning offers a safe alternative for decision-making in deep biomedical models, even with uncertain data. This approach aids in areas like diabetes diagnosis and drug design.

Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Artificial Intelligence in Medicine

Background:

  • Deep biomedical models, often based on differential equations, present challenges in decision-making due to non-linearity and data uncertainty.
  • Existing methods struggle to provide reliable insights when faced with inherent variability in biomedical data.

Purpose of the Study:

  • To introduce a novel constraint reasoning framework designed to enhance safe decision-making processes for deep biomedical models.
  • To address the limitations of traditional approaches in handling uncertainty within complex biological systems.

Main Methods:

  • Utilized generic constraint propagation techniques to reduce uncertainty bounds for numerical variables.
  • Developed specialized constraint reasoning methods tailored for handling differential equations in biomedical contexts.

Related Experiment Videos

Main Results:

  • Successfully applied the framework to diverse biomedical models, including diabetes diagnosis, drug design optimization, and epidemiological studies.
  • Demonstrated the framework's efficacy as a decision-support tool, providing valuable insights despite significant data uncertainty.

Conclusions:

  • Constraint reasoning presents a viable and potentially superior alternative to conventional simulation methods for biomedical decision support.
  • The proposed framework is particularly beneficial when the requirement for safe and reliable decisions is paramount in complex biomedical applications.