5 papers
TRACE: A Concept Bottleneck Model for Longitudinal 3D Glioblastoma Response Assessment
Alia Tarek, Hamsa Saberr, Hamza Elghonemy +6
Longitudinal glioblastoma response assessment requires comparing subtle tumor changes across MRI time points using structured clinical criteria such as RANO. However, most deep lea…
AuditCopilot: Leveraging LLMs for Fraud Detection in Double-Entry Bookkeeping
Md Abdul Kadir, Sai Suresh Macharla Vasu, Sidharth S. Nair +1
Auditors rely on Journal Entry Tests (JETs) to detect anomalies in tax-related ledger records, but rule-based methods generate overwhelming false positives and struggle with subtle…
CBM-RAG: Demonstrating Enhanced Interpretability in Radiology Report Generation with Multi-Agent RAG and Concept Bottleneck Models
Hasan Md Tusfiqur Alam, Devansh Srivastav, Abdulrahman Mohamed Selim +3
Advancements in generative Artificial Intelligence (AI) hold great promise for automating radiology workflows, yet challenges in interpretability and reliability hinder clinical ad…
Enhancing Online Learning Efficiency Through Heterogeneous Resource Integration with a Multi-Agent RAG System
Devansh Srivastav, Hasan Md Tusfiqur Alam, Afsaneh Asaei +3
Efficient online learning requires seamless access to diverse resources such as videos, code repositories, documentation, and general web content. This poster paper introduces earl…
Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAG
Hasan Md Tusfiqur Alam, Devansh Srivastav, Md Abdul Kadir +1
Deep learning has advanced medical image classification, but interpretability challenges hinder its clinical adoption. This study enhances interpretability in Chest X-ray (CXR) cla…