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

You might also read

Related Articles

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

Sort by
Same author

The vertical symphony: how pitch perception shapes spatial and affective mapping across different countries.

Cognitive processing·2026
Same author

Effects of Appearance Preoccupation and Safety Behaviors in Body Dysmorphic Disorder: An Ecological Momentary Assessment Study.

Behavior therapy·2026
Same author

Associations Among in-The-Moment Emotional Clarity, Emotion Regulation, and Psychopathology in Obsessive-Compulsive Disorder.

Depression and anxiety·2025
Same author

Modelling dependent censoring in time-to-event data using boosting copula regression.

Lifetime data analysis·2025
Same author

Deep Mixture of Linear Mixed Models for Complex Longitudinal Data.

Statistics in medicine·2025
Same author

Boosting distributional copula regression for bivariate binary, discrete and mixed responses.

Statistical methods in medical research·2025
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
Same journal

Self-Supervised Continuous Dynamic Graph Representation Learning via Hawkes Processes.

IEEE transactions on neural networks and learning systems·2026
Same journal

cPU: Consistent Risk Estimator for Positive-Unlabeled Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing.

IEEE transactions on neural networks and learning systems·2026
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2025

Animal Models of Depression - Chronic Despair Model CDM
05:47

Animal Models of Depression - Chronic Despair Model CDM

Published on: September 23, 2021

7.2K

The Deep Promotion Time Cure Model.

Victor Medina-Olivares, Stefan Lessmann, Nadja Klein

    IEEE Transactions on Neural Networks and Learning Systems
    |May 21, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel deep learning method for predicting time-to-event data with cure fractions. The flexible survival model within a deep neural network (DNN) framework improves prediction accuracy and covariate effect interpretation.

    More Related Videos

    An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth
    09:14

    An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth

    Published on: August 11, 2011

    15.9K
    An In Vitro Dormancy Model of Estrogen-sensitive Breast Cancer in the Bone Marrow: A Tool for Molecular Mechanism Studies and Hypothesis Generation
    08:48

    An In Vitro Dormancy Model of Estrogen-sensitive Breast Cancer in the Bone Marrow: A Tool for Molecular Mechanism Studies and Hypothesis Generation

    Published on: June 30, 2015

    8.2K

    Related Experiment Videos

    Last Updated: Jun 25, 2025

    Animal Models of Depression - Chronic Despair Model CDM
    05:47

    Animal Models of Depression - Chronic Despair Model CDM

    Published on: September 23, 2021

    7.2K
    An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth
    09:14

    An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth

    Published on: August 11, 2011

    15.9K
    An In Vitro Dormancy Model of Estrogen-sensitive Breast Cancer in the Bone Marrow: A Tool for Molecular Mechanism Studies and Hypothesis Generation
    08:48

    An In Vitro Dormancy Model of Estrogen-sensitive Breast Cancer in the Bone Marrow: A Tool for Molecular Mechanism Studies and Hypothesis Generation

    Published on: June 30, 2015

    8.2K

    Area of Science:

    • Biostatistics
    • Machine Learning
    • Survival Analysis

    Background:

    • Predicting time-to-event data with cure fractions is challenging.
    • Existing methods may struggle with complex relationships and high-dimensional data.

    Purpose of the Study:

    • To develop a novel deep neural network (DNN) framework for flexible survival models.
    • To accurately predict time-to-event data in the presence of cure fractions.
    • To capture nonlinear relationships and high-dimensional interactions.

    Main Methods:

    • Integration of flexible survival models into a deep neural network (DNN).
    • Utilized an orthogonalization layer for predictor identifiability.
    • Additive decomposition of linear, nonlinear, and interaction effects.

    Main Results:

    • Demonstrated superior predictive performance compared to existing methods.
    • Achieved computational efficiency through simulations.
    • Applied successfully to a large U.S. mortgage loan dataset.

    Conclusions:

    • The proposed DNN-based flexible survival model offers enhanced predictive accuracy.
    • The method provides a more realistic understanding of covariate effects in survival data.
    • This approach is suitable for large-scale applications in biostatistics and finance.