Challenges for Predictive Modeling with Neural Network Techniques using Error-Prone Dietary Intake Data

no code implementations • 15 Nov 2023 • Dylan Spicker, Amir Nazemi, Joy Hutchinson, Paul Fieguth, Sharon I. Kirkpatrick, Michael Wallace, Kevin W. Dodd

In this work, we demonstrate the ways in which measurement error erodes the performance of neural networks, and illustrate the care that is required for leveraging these models in the presence of error.

Radiomics Boosts Deep Learning Model for IPMN Classification

no code implementations • 11 Sep 2023 • Lanhong Yao, Zheyuan Zhang, Ugur Demir, Elif Keles, Camila Vendrami, Emil Agarunov, Candice Bolan, Ivo Schoots, Marc Bruno, Rajesh Keswani, Frank Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Michael Wallace, Concetto Spampinato, Ulas Bagci

We test our proposed decision-fusion model in multi-center data sets of 246 multi-contrast MRI scans and obtain superior performance to the state of the art (SOTA) in this field.

Classification Decision Making

A Critical Appraisal of Data Augmentation Methods for Imaging-Based Medical Diagnosis Applications

no code implementations • 14 Dec 2022 • Tara M. Pattilachan, Ugur Demir, Elif Keles, Debesh Jha, Derk Klatte, Megan Engels, Sanne Hoogenboom, Candice Bolan, Michael Wallace, Ulas Bagci

Current data augmentation techniques and transformations are well suited for improving the size and quality of natural image datasets but are not yet optimized for medical imaging.

Data Augmentation Medical Diagnosis

PAN: Projective Adversarial Network for Medical Image Segmentation

no code implementations • 11 Jun 2019 • Naji Khosravan, Aliasghar Mortazi, Michael Wallace, Ulas Bagci

Adversarial learning has been proven to be effective for capturing long-range and high-level label consistencies in semantic segmentation.

Image Segmentation Pancreas Segmentation +2