Looking Beyond What You See: An Empirical Analysis on Subgroup Intersectional Fairness for Multi-label Chest X-ray Classification Using Social Determinants of Racial Health Inequities

no code implementations • 27 Mar 2024 • Dana Moukheiber, Saurabh Mahindre, Lama Moukheiber, Mira Moukheiber, Mingchen Gao

In this study, we propose a framework to achieve accurate diagnostic outcomes and ensure fairness across intersectional groups in high-dimensional chest X- ray multi-label classification.

Fairness Multi-Label Classification

DengueNet: Dengue Prediction using Spatiotemporal Satellite Imagery for Resource-Limited Countries

1 code implementation • 20 Jan 2024 • Kuan-Ting Kuo, Dana Moukheiber, Sebastian Cajas Ordonez, David Restrepo, Atika Rahman Paddo, Tsung-Yu Chen, Lama Moukheiber, Mira Moukheiber, Sulaiman Moukheiber, Saptarshi Purkayastha, Po-Chih Kuo, Leo Anthony Celi

In this study, our aim is to improve health equity in resource-constrained countries by exploring the effectiveness of high-resolution satellite imagery as a nontraditional and readily accessible data source.

Early Diagnosis of Chronic Obstructive Pulmonary Disease from Chest X-Rays using Transfer Learning and Fusion Strategies

no code implementations • 13 Nov 2022 • Ryan Wang, Li-Ching Chen, Lama Moukheiber, Mira Moukheiber, Dana Moukheiber, Zach Zaiman, Sulaiman Moukheiber, Tess Litchman, Kenneth Seastedt, Hari Trivedi, Rebecca Steinberg, Po-Chih Kuo, Judy Gichoya, Leo Anthony Celi

We further propose two fusion schemes, (1) model-level fusion, including bagging and stacking methods using MIMIC-CXR, and (2) data-level fusion, including multi-site data using MIMIC-CXR and Emory-CXR, and multi-modal using MIMIC-CXRs and MIMIC-IV EHR, to improve the overall model performance.

Fairness Transfer Learning