A Persona-Based Corpus in the Diabetes Self-Care Domain - Applying a Human-Centered Approach to a Low-Resource Context (2024.lrec-main)
Copied to clipboard
| Challenge: | Human-centered design (HCD) is a new approach to natural language processing that uses personas, user profiles and other tools to build corpus. |
| Approach: | They propose to use personas to model interpersonal interaction in a healthcare domain to follow an HCD approach. |
| Outcome: | The proposed model improves the quality of human-centered design in a healthcare domain and overcomes the lack of in-depth human-centricity in the field. |
Similar Papers
On The Persona-based Summarization of Domain-Specific Documents (2024.findings-acl)
Copied to clipboard
Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Bhowmick, Pawan Goyal, Niloy Ganguly, Prasenjit Dey, Ravi Kokku
| Challenge: | In an ever-expanding world of domain-specific knowledge, summarization of information is a complex task . persona-based summarizing of domain specific information by humans is deemed not preferred . |
| Approach: | They propose a framework for efficient training of a small foundation LLM on a healthcare corpus. |
| Outcome: | The proposed framework fine-tunes a domain-specific small foundation LLM using a healthcare corpus and evaluates its quality using AI-based critiquing. |
CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models (2023.eacl-main)
Copied to clipboard
| Challenge: | Existing studies show that pretrained language models can act as knowledge bases and reason like humans. |
| Approach: | They propose to use pretrained language models to generate free-flow textual explanations about 52 health conditions across three clinical dimensions. |
| Outcome: | The proposed model can generate concise and readable text, but can be improved on medical accuracy and QA. |
DualAlign: Generating Clinically Grounded Synthetic Data (2026.findings-acl)
Copied to clipboard
| Challenge: | Large language models (LLMs) can generate fluent clinical text, but ensuring that such outputs are clinically grounded and useful for downstream modeling remains challenging. |
| Approach: | They propose a disease-agnostic framework for generating privacy-preserving, clinically faithful synthetic EHR narratives. |
| Outcome: | The proposed framework produces context-aware, symptom-rich sentences that more closely reflect real-world clinical documentation. |
Applications of Natural Language Processing in Clinical Research and Practice (N19-5)
Copied to clipboard
| Challenge: | a tutorial on clinical NLP will introduce students and experts to the field . a focus will be on the use of clinical Nlp in clinical research and practice . |
| Approach: | This tutorial introduces the clinical use of natural language processing (NLP) techniques . it will review techniques and tools developed for the clinical domain . |
| Outcome: | This tutorial will introduce the clinical NLP methodologies and tools at two top universities . the goal of the tutorial is to encourage NLP researchers in the general domain to contribute . |
Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency (2025.emnlp-main)
Copied to clipboard
Svetlana Maslenkova, Clement Christophe, Marco AF Pimentel, Tathagata Raha, Muhammad Umar Salman, Ahmed Al Mahrooqi, Avani Gupta, Shadab Khan, Ronnie Rajan, Praveenkumar Kanithi
| Challenge: | Current dataset curation and bias assessment practices lack transparency . current approaches lack a thorough understanding of how data characteristics influence model behavior . |
| Approach: | They propose a comprehensive bias evaluation framework that integrates general benchmarks with a healthcare-specific methodology to probe for biases in a sensitive healthcare context. |
| Outcome: | The proposed approach to bias evaluation leverages established benchmarks and a healthcare-specific methodology. |
Incorporating medical knowledge in BERT for clinical relation extraction (2021.emnlp-main)
Copied to clipboard
| Challenge: | Pre-trained language models (PLMs) are used for diverse NLP tasks such as Information Extraction, Sentiment Analysis and Question/Answering. |
| Approach: | They propose to add medical knowledge to pre-trained language models to facilitate clinical relation extraction using a large text corpus. |
| Outcome: | The proposed model outperforms the state-of-the-art systems on the benchmark i2b2/VA 2010 clinical relation extraction dataset. |
A Semi-autonomous System for Creating a Human-Machine Interaction Corpus in Virtual Reality: Application to the ACORFORMed System for Training Doctors to Break Bad News (L18-1)
Copied to clipboard
Magalie Ochs, Philippe Blache, Grégoire de Montcheuil, Jean-Marie Pergandi, Jorane Saubesty, Daniel Francon, Daniel Mestre
| Challenge: | Existing methods for training doctors to break bad news are expensive and time consuming. |
| Approach: | They propose a method to collect a corpus of human-machine interactions and then construct a semi-autonomous system based on the collected corpus. |
| Outcome: | The proposed system is based on a corpus-based method to analyze human-machine interactions and then develop fully autonomous prototype. |
CHiRPE: A Step Towards Real-World Clinical NLP with Clinician-Oriented Model Explanations (2026.eacl-short)
Copied to clipboard
Stephanie Fong, Zimu Wang, Guilherme C Oliveira, Xiangyu Zhao, Yiwen Jiang, Jiahe Liu, Beau-Luke Colton, Scott W. Woods, Martha Shenton, Barnaby Nelson, Zongyuan Ge, Dominic Dwyer
| Challenge: | Psychotic disorders are a major contributor to the global health burden due to their relatively high mortality risk. |
| Approach: | They propose an NLP pipeline that takes semi-structured clinical interviews to predict psychosis risk and generate novel SHAP explanation formats. |
| Outcome: | The proposed pipeline outperforms baseline models and achieves 90% accuracy across three BERT variants. |
Designing, Evaluating, and Learning from Humans Interacting with NLP Models (2023.emnlp-tutorial)
Copied to clipboard
| Challenge: | This tutorial will cover how to conduct human-in-the-loop usability evaluations to ensure that models are capable of interacting with humans. |
| Approach: | They will provide a systematic overview of key considerations and effective approaches for studying human-NLP model interactions. |
| Outcome: | This tutorial will cover how to conduct human-in-the-loop usability evaluations to ensure that models are capable of interacting with humans. |
Human-Centered Evaluation of Language Technologies (2024.emnlp-tutorials)
Copied to clipboard
| Challenge: | a lack of human-centered considerations about people’s needs for language technologies is causing an “evaluation crisis” in NLP. |
| Approach: | This tutorial introduces perspectives and methodologies from human-computer interaction (HCI) it will introduce what to evaluate for, how generalizable the results are to the real-world contexts, and pragmatic costs to conduct the evaluation. |
| Outcome: | This tutorial introduces perspectives and methodologies from human-computer interaction (HCI) the tutorial will also encourage reflection on how these HCI perspectives and methods can complement NLP evaluation through Q&A discussions and a hands-on exercise. |