Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection. - Khashayar Namdar; Isha Gujrathi; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning. - Partoo Vafaeikia; Khashayar Namdar; Farzad Khalvati (CoRR, 2020)

A Transfer Learning-Based Active Learning Framework for Brain Tumor Classification. - Ruqian Hao; Khashayar Namdar; Lin Liu; Farzad Khalvati (Frontiers Artif. Intell., 2021)

A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account. - Khashayar Namdar; Masoom A. Haider; Farzad Khalvati (Frontiers Artif. Intell., 2021)

A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-Weighted MRI Using Convolutional Neural Networks. - Ruqian Hao; Khashayar Namdar; Lin Liu; Masoom A. Haider; Farzad Khalvati (J. Digit. Imaging, 2021)

Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators. - Akino Watanabe; Sara Ketabi; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology. - Pranav Agnihotri; Sara Ketabi; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning. - Khashayar Namdar; Partoo Vafaeikia; Farzad Khalvati (CoRR, 2022)

Superpixel Generation and Clustering for Weakly Supervised Brain Tumor Segmentation in MR Images. - Jay J. Yoo; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI. - Khashayar Namdar; Matthias W. Wagner; Kareem Kudus; Cynthia Hawkins; Uri Tabori; Birgit Ertl-Wagner; Farzad Khalvati (CoRR, 2022)

A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images. - Jay J. Yoo; Khashayar Namdar; Matthias W. Wagner; Liana Nobre; Uri Tabori; Cynthia Hawkins; Birgit B. Ertl-Wagner; Farzad Khalvati (CoRR, 2022)

A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection. - Jay J. Yoo; Khashayar Namdar; Chris McIntosh; Farzad Khalvati; Patrik Rogalla (CoRR, 2022)

Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification. - Sara Ketabi; Pranav Agnihotri; Hamed Zakeri; Khashayar Namdar; Farzad Khalvati (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour Classification. - Sajith Rajapaksa; Khashayar Namdar; Farzad Khalvati (MILLanD@MICCAI, 2023)

Advanced Receiver Operating Characteristic Curve Analysis to Identify Outliers in Binary Machine Learning Classifications for Precision Medicine. - Khashayar Namdar; Farzad Khalvati (BHI, 2024)

Improving Interpretability of Radiology Report-based Pediatric Brain Tumor Pathology Classification and Key-phrases Extraction Using Large Language Models. - Chen Zhao; Kareem Kudus; Sara Ketabi; Khashayar Namdar; Matthias W. Wagner; Birgit B. Ertl-Wagner; Farzad Khalvati (BHI, 2024)

Anomaly Detection in Pediatric and Adults Brain MRI with Generative Model. - Chaojun Chen; Khashayar Namdar; Matthias W. Wagner; Birgit B. Ertl-Wagner; Farzad Khalvati (EMBC, 2024)

Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation. - Chaojun Chen; Khashayar Namdar; Yujie Wu; Shahob Hosseinpour; Manohar Shroff; Andrea Doria 001; Farzad Khalvati (EMBC, 2024)

Deep superpixel generation and clustering for weakly supervised segmentation of brain tumors in MR images. - Jay J. Yoo; Khashayar Namdar; Farzad Khalvati (BMC Medical Imaging, 2024)

Improving Pediatric Low-Grade Neuroepithelial Tumors Molecular Subtype Identification Using a Novel AUROC Loss Function for Convolutional Neural Networks. - Khashayar Namdar; Matthias W. Wagner; Cynthia Hawkins; Uri Tabori; Birgit B. Ertl-Wagner; Farzad Khalvati (CoRR, 2024)

Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad. - Arash Rasti-Meymandi; Zahra Hosseini; Sina Davari; Abolfazl Moshiri; Shabnam Rahimi-Golkhandan; Khashayar Namdar; Nikta Feizi; Mohamad Tavakoli-Targhi; Farzad Khalvati (CoRR, 2024)

Red Teaming Large Language Models for Healthcare. - Vahid Balazadeh Meresht; Michael Cooper; David Pellow; Atousa Assadi; Jennifer Bell; Jim Fackler; Gabriel Funingana; Spencer Gable-Cook; Anirudh Gangadhar; Abhishek Jaiswal; Sumanth Kaja; Christopher Khoury; et al. (CoRR, 2025)

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking. - Connor Ludwig; Khashayar Namdar; Farzad Khalvati (CoRR, 2025)

Non-invasive liver fibrosis screening on CT images using radiomics. - Jay J. Yoo; Khashayar Namdar; Sean Carey; Sandra E. Fischer; Chris McIntosh; Farzad Khalvati; Patrik Rogalla (BMC Medical Imaging, 2025)