Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications

N Mulla, P Gharpure - Progress in Artificial Intelligence, 2023 - Springer
Question generation in natural language has a wide variety of applications. It can be a
helpful tool for chatbots for generating interesting questions as also for automating the …

Prompt engineering for healthcare: Methodologies and applications

J Wang, E Shi, S Yu, Z Wu, C Ma, H Dai, Q Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
Prompt engineering is a critical technique in the field of natural language processing that
involves designing and optimizing the prompts used to input information into models, aiming …

Medalign: A clinician-generated dataset for instruction following with electronic medical records

SL Fleming, A Lozano, WJ Haberkorn… - Proceedings of the …, 2024 - ojs.aaai.org
The ability of large language models (LLMs) to follow natural language instructions with
human-level fluency suggests many opportunities in healthcare to reduce administrative …

Ehrxqa: A multi-modal question answering dataset for electronic health records with chest x-ray images

S Bae, D Kyung, J Ryu, E Cho, G Lee… - Advances in …, 2024 - proceedings.neurips.cc
Abstract Electronic Health Records (EHRs), which contain patients' medical histories in
various multi-modal formats, often overlook the potential for joint reasoning across imaging …

Paniniqa: Enhancing patient education through interactive question answering

P Cai, Z Yao, F Liu, D Wang, M Reilly… - Transactions of the …, 2023 - direct.mit.edu
A patient portal allows discharged patients to access their personalized discharge
instructions in electronic health records (EHRs). However, many patients have difficulty …

EHRNoteQA: A Patient-Specific Question Answering Benchmark for Evaluating Large Language Models in Clinical Settings

S Kweon, J Kim, H Kwak, D Cha, H Yoon, K Kim… - arXiv preprint arXiv …, 2024 - arxiv.org
This study introduces EHRNoteQA, a novel patient-specific question answering benchmark
tailored for evaluating Large Language Models (LLMs) in clinical environments. Based on …

Question Answering for Electronic Health Records: A Scoping Review of datasets and models

J Bardhan, K Roberts, DZ Wang - arXiv preprint arXiv:2310.08759, 2023 - arxiv.org
Question Answering (QA) systems on patient-related data can assist both clinicians and
patients. They can, for example, assist clinicians in decision-making and enable patients to …

Deep-Learning-Driven Techniques for Real-Time Multimodal Health and Physical Data Synthesis

MS Haleem, A Ekuban, A Antonini, S Pagliara… - Electronics, 2023 - mdpi.com
With the advent of Artificial Intelligence for healthcare, data synthesis methods present
crucial benefits in facilitating the fast development of AI models while protecting data …

Towards scalable structured data from clinical text

M Agrawal - 2023 - dspace.mit.edu
The adoption of electronic health records (EHRs) presents an incredible opportunity to
improve medicine both at the point-of-care and through retrospective research …

Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework

R Averly, X Ning - arXiv preprint arXiv:2407.04629, 2024 - arxiv.org
Clinical named entity recognition (NER) aims to retrieve important entities within clinical
narratives. Recent works have demonstrated that large language models (LLMs) can …