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

Filters

Matthew Schabath

Showing results (1-10 of 11) with videos related to

Pageof 2
Sort By:
Biorxiv : the Preprint Server for Biology|December 15, 2025
Advancements in an Automated Breast Density Detection Technique for Breast Cancer Risk Prediction: a Synthetic Signal-dependent Noise ConstructJohn Heine, Erin Fowler, Matthew Schabath, et al.
Computers in Biology and Medicine|July 14, 2020
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the futureRahul Paul, Matthew Schabath, Robert Gillies, et al.
Proceedings of ... International Joint Conference on Neural Networks. International Joint Conference on Neural Networks|November 17, 2018
Predicting Nodule Malignancy using a CNN Ensemble ApproachRahul Paul, Lawrence Hall, Dmitry Goldgof, et al.
Scientific Reports|March 16, 2019
Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and AggressivenessDmitry Cherezov, Dmitry Goldgof, Lawrence Hall, et al.
Journal of Imaging Informatics in Medicine|November 11, 2025
Detection of Confounders and Potential Confounders in Computed Tomography Lung DatasetsNikolai Fetisov, Wai Lone Jonathan Ho, Ghada Zamzmi, et al.
Tomography (Ann Arbor, Mich.)|May 5, 2021
A Radiogenomics Ensemble to Predict EGFR and KRAS Mutations in NSCLCSilvia Moreno, Mario Bonfante, Eduardo Zurek, et al.
Proceedings of ... International Joint Conference on Neural Networks. International Joint Conference on Neural Networks|November 17, 2018
Representation of Deep Features using Radiologist defined Semantic FeaturesRahul Paul, Ying Liu, Qian Li, et al.
AIDS Research and Human Retroviruses|May 3, 2023
Lung Cancer Screening Adherence Among People with HIV Treated at an Integrated Health System in FloridaJessica Y Islam, Shuang Yang, Matthew Schabath, et al.
Tomography (Ann Arbor, Mich.)|March 12, 2019
Explaining Deep Features Using Radiologist-Defined Semantic Features and Traditional Quantitative FeaturesRahul Paul, Matthew Schabath, Yoganand Balagurunathan, et al.
Preventive Medicine Reports|August 7, 2023
Lung cancer screening adherence among people living with and without HIV: An analysis of an integrated health system in Florida, United States (2012-2021)Jessica Y Islam, Shuang Yang, Matthew Schabath, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Biorxiv : the Preprint Server for Biology|December 15, 2025
Advancements in an Automated Breast Density Detection Technique for Breast Cancer Risk Prediction: a Synthetic Signal-dependent Noise ConstructJohn Heine, Erin Fowler, Matthew Schabath, et al.
Computers in Biology and Medicine|July 14, 2020
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the futureRahul Paul, Matthew Schabath, Robert Gillies, et al.
Proceedings of ... International Joint Conference on Neural Networks. International Joint Conference on Neural Networks|November 17, 2018
Predicting Nodule Malignancy using a CNN Ensemble ApproachRahul Paul, Lawrence Hall, Dmitry Goldgof, et al.
Scientific Reports|March 16, 2019
Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and AggressivenessDmitry Cherezov, Dmitry Goldgof, Lawrence Hall, et al.
Journal of Imaging Informatics in Medicine|November 11, 2025
Detection of Confounders and Potential Confounders in Computed Tomography Lung DatasetsNikolai Fetisov, Wai Lone Jonathan Ho, Ghada Zamzmi, et al.
Tomography (Ann Arbor, Mich.)|May 5, 2021
A Radiogenomics Ensemble to Predict EGFR and KRAS Mutations in NSCLCSilvia Moreno, Mario Bonfante, Eduardo Zurek, et al.
Proceedings of ... International Joint Conference on Neural Networks. International Joint Conference on Neural Networks|November 17, 2018
Representation of Deep Features using Radiologist defined Semantic FeaturesRahul Paul, Ying Liu, Qian Li, et al.
AIDS Research and Human Retroviruses|May 3, 2023
Lung Cancer Screening Adherence Among People with HIV Treated at an Integrated Health System in FloridaJessica Y Islam, Shuang Yang, Matthew Schabath, et al.
Tomography (Ann Arbor, Mich.)|March 12, 2019
Explaining Deep Features Using Radiologist-Defined Semantic Features and Traditional Quantitative FeaturesRahul Paul, Matthew Schabath, Yoganand Balagurunathan, et al.
Preventive Medicine Reports|August 7, 2023
Lung cancer screening adherence among people living with and without HIV: An analysis of an integrated health system in Florida, United States (2012-2021)Jessica Y Islam, Shuang Yang, Matthew Schabath, et al.
Pageof 2