5 papers
Click, Predict, Trust: Clinician-in-the-Loop AI Segmentation for Lung Cancer CT-Based Prognosis within the Knowledge-to-Action Framework
Mohammad R. Salmanpour, Sonya Falahati, Amir Hossein Pouria +10
Lung cancer remains the leading cause of cancer mortality, with CT imaging central to screening, prognosis, and treatment. Manual segmentation is variable and time-intensive, while…
AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning
Morteza Alizadeh, Mehrdad Oveisi, Sonya Falahati +6
Machine learning (ML) models rely heavily on consistent and accurate performance metrics to evaluate and compare their effectiveness. However, existing libraries often suffer from…
Pathobiological Dictionary Defining Pathomics and Texture Features: Addressing Understandable AI Issues in Personalized Liver Cancer; Dictionary Version LCP1.0
Mohammad R. Salmanpour, Seyed Mohammad Piri, Somayeh Sadat Mehrnia +5
Artificial intelligence (AI) holds strong potential for medical diagnostics, yet its clinical adoption is limited by a lack of interpretability and generalizability. This study int…
Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0
Mohammad R. Salmanpour, Sajad Amiri, Sara Gharibi +5
We investigate the connection between visual semantic features defined in PI-RADS and associated risk factors, moving beyond abnormal imaging findings, establishing a shared framew…
Enhanced Lung Cancer Survival Prediction using Semi-Supervised Pseudo-Labeling and Learning from Diverse PET/CT Datasets
Mohammad R. Salmanpour, Arman Gorji, Amin Mousavi +7
Objective: This study explores a semi-supervised learning (SSL), pseudo-labeled strategy using diverse datasets to enhance lung cancer (LCa) survival predictions, analyzing Handcra…