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Found 5 papers, 0 papers with code
Leveraging A Medical Knowledge Graph into Large Language Models for Diagnosis Prediction
In this paper, we outline an innovative approach for augmenting the proficiency of LLMs in the realm of automated diagnosis generation, achieved through the incorporation of a medical knowledge graph (KG) and a novel graph model: Dr. Knows, inspired by the clinical diagnostic reasoning process.
Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes
The BioNLP Workshop 2023 initiated the launch of a shared task on Problem List Summarization (ProbSum) in January 2023.
Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning
Generative artificial intelligence (AI) is a promising direction for augmenting clinical diagnostic decision support and reducing diagnostic errors, a leading contributor to medical errors.
Summarizing Patients Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models
In this work, we propose a new NLP task that aims to generate a list of problems in a patient's daily care plan using input from the provider's progress notes during hospitalization.
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding
This work introduces a hierarchical annotation schema with three stages to address clinical text understanding, clinical reasoning, and summarization.
