Noise and rank-dependent geometrical filter improves sensitivity of highly specific discovery by microarrays. - Hassan M. Fathallah-Shaykh (Bioinform., 2005)

Inference of genetic regulatory networks using regularized likelihood with covariance estimation. - Ghulam Rasool 001; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh; Dan Schonfeld (SSP, 2012)

Compressive Kalman filtering for recovering temporally-rewiring genetic networks. - Jehandad Khan; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh (EUSIPCO, 2013)

Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother. - Jehandad Khan; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh (EURASIP J. Bioinform. Syst. Biol., 2014)

Proper orthogonal decomposition for parameter estimation in oscillating biological networks. - Amanda M. Rehm; Elizabeth Y. Scribner; Hassan M. Fathallah-Shaykh (J. Comput. Appl. Math., 2014)

Level set segmentation using non-negative matrix factorization of brain MRI images. - Dimah Dera; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh (BIBM, 2015)

Non-negative matrix factorization for non-parametric and unsupervised image clustering and segmentation. - Dimah Dera; Nidhal Bouaynaya; Robi Polikar; Hassan M. Fathallah-Shaykh (IJCNN, 2016)

Interactive Semi-automated Method Using Non-negative Matrix Factorization and Level Set Segmentation for the BRATS Challenge. - Dimah Dera; Fabio Raman; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh (BrainLes@MICCAI, 2016)

The AKRON-Kalman filter for tracking time-varying networks. - Victor Carluccio; Nidhal Bouaynaya; Gregory Ditzler; Hassan M. Fathallah-Shaykh (BHI, 2017)

Nonlinear Brain Tumor Model Estimation with Long Short-Term Memory Neural Networks. - Jiashu Guo; Zhengzhong Liang; Gregory Ditzler; Nidhal C. Bouaynaya; Elizabeth Y. Scribner; Hassan M. Fathallah-Shaykh (IJCNN, 2018)

Inverted Cone Convolutional Neural Network For Deboning MRIs. - Oliver Palumbo; Dimah Dera; Nidhal C. Bouaynaya; Hassan M. Fathallah-Shaykh (IJCNN, 2018)

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. - Spyridon Bakas; Mauricio Reyes 001; András Jakab; Stefan Bauer; Markus Rempfler; Alessandro Crimi; Russell Takeshi Shinohara; Christoph Berger; Sung Min Ha; Martin Rozycki; Marcel Prastawa; Esther Alberts; et al. (CoRR, 2018)

Inception Modules Enhance Brain Tumor Segmentation. - Daniel E. Cahall; Ghulam Rasool 001; Nidhal C. Bouaynaya; Hassan M. Fathallah-Shaykh (Frontiers Comput. Neurosci., 2019)

The Federated Tumor Segmentation (FeTS) Challenge. - Sarthak Pati; Ujjwal Baid; Maximilian Zenk; Brandon Edwards; Micah J. Sheller; G. Anthony Reina; Patrick Foley; Alexey Gruzdev; Jason Martin; Shadi Albarqouni; Yong Chen 016; Russell Taki Shinohara; et al. (CoRR, 2021)

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification. - Ujjwal Baid; Satyam Ghodasara; Michel Bilello; Suyash Mohan; Evan Calabrese; Errol Colak; Keyvan Farahani; Jayashree Kalpathy-Cramer; Felipe C. Kitamura; Sarthak Pati; Luciano M. Prevedello; Jeffrey D. Rudie; et al. (CoRR, 2021)

Dilated Inception U-Net (DIU-Net) for Brain Tumor Segmentation. - Daniel E. Cahall; Ghulam Rasool 001; Nidhal C. Bouaynaya; Hassan M. Fathallah-Shaykh (CoRR, 2021)

Trustworthy Medical Segmentation with Uncertainty Estimation. - Giuseppina Carannante; Dimah Dera; Nidhal C. Bouaynaya; Ghulam Rasool 001; Hassan M. Fathallah-Shaykh (CoRR, 2021)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - Raghav Mehta; Angelos Filos; Ujjwal Baid; Chiharu Sako; Richard McKinley; Michael Rebsamen; Katrin Dätwyler; Raphael Meier; Piotr Radojewski; Gowtham Krishnan Murugesan; Sahil S. Nalawade; Chandan Ganesh; et al. (CoRR, 2021)

PremiUm-CNN: Propagating Uncertainty Towards Robust Convolutional Neural Networks. - Dimah Dera; Nidhal Carla Bouaynaya; Ghulam Rasool 001; Roman Shterenberg; Hassan M. Fathallah-Shaykh (IEEE Trans. Signal Process., 2021)

Deep Learning for Audio Visual Emotion Recognition. - Tassadaq Hussain; Wenwu Wang 001; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh; Lyudmila Mihaylova (FUSION, 2022)

EvalAttAI: A Holistic Approach to Evaluating Attribution Maps in Robust and Non-Robust Models. - Ian E. Nielsen; Ravi Prakash Ramachandran; Nidhal Bouaynaya; Hassan M. Fathallah-Shaykh; Ghulam Rasool 001 (IEEE Access, 2023)

The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting. - Florian Kofler; Felix Meissen; Felix Steinbauer; Robert Graf; Eva Oswald; Ezequiel de la Rosa; Hongwei Bran Li; Ujjwal Baid; Florian A. Hölzl; Özgün Turgut; Izabela Horvath; Diana Waldmannstetter; et al. (CoRR, 2023)

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn). - Hongwei Bran Li; Gian Marco Conte; Syed Muhammad Anwar; Florian Kofler; Koen Van Leemput; Marie Piraud; Ivan Ezhov; Felix Meissen; Maruf Adewole; Anastasia Janas; Anahita Fathi Kazerooni; Dominic LaBella; et al. (CoRR, 2023)