TriMediQ is proposed, a triplet-structured approach that converts patient responses into triplets, aggregates them into a patient-specific knowledge graph, and injects structured representations into a doctor agent via a trainable projection module, demonstrating that structured knowledge representations provide an effective approach for interactive medical QA.
SABET-QA is proposed, a framework that iteratively refines reasoning states across multiple hops via a bidirectional entity-temporal scoring mechanism and a slot-aware contextualization module that aligns question semantics with temporal KG embeddings.
A novel multimodal RAG framework tailored for MedVQA is proposed, which leverages multimodal data, including medical images, reports, and generated captions, to provide more accurate clinical answers, and introduces a training paradigm that uses captions as auxiliary supervision, enhancing cross-modal alignment via con...
Mai A. Shaaban, M. Zarei, Adnan Khan et al.· 0 citations
Retrieving past similar dialogues to assist response generation in the present context is a promising approach to addressing the shortage of highly experienced professionals in various domains, such as user support and mental health counseling. However, unlike traditional retrieval, this task requires finding dialogue...
This work proposes Knowledge Graph for Question Generation (KG4QG), a novel framework that integrates knowledge graphs with large language models to address the challenges of MHQG, and demonstrates the effectiveness of combining structured knowledge and pre-trained language models for complex question generation tasks.
Yllias Chali, Al Hasib Mahamud· International Conference on...· 0 citations
The results show that the strongest systems move beyond single-pass prompting and instead rely on structured evidence extraction, retrieval, verification, and orchestration across multiple components.
Artemis Llabrés, Marc Serra Ortega, Tomàs Ockier et al.· Lecture Notes in Computer Sc...· 1 citation
Evaluations of fifteen LLM doctor agents show that moving from a single-turn diagnosis on the standardized records to multi-turn consultations causes large degradations, highlighting equity risks that single-turn benchmarks miss.
Youssef Mohamed, Ahmed Heakl, Qin-Rong Cui et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
