[HTML][HTML] Extracting medical information from free-text and unstructured patient-generated health data using natural language processing methods: feasibility study with …
Background Patient-generated health data (PGHD) captured via smart devices or digital
health technologies can reflect an individual health journey. PGHD enables tracking and …
health technologies can reflect an individual health journey. PGHD enables tracking and …
Grammar-constrained decoding for structured information extraction with fine-tuned generative models applied to clinical trial abstracts
Background In the field of structured information extraction, there are typically semantic and
syntactic constraints on the output of information extraction (IE) systems. These constraints …
syntactic constraints on the output of information extraction (IE) systems. These constraints …
Advancing machine learning with OCR2SEQ: an innovative approach to multi-modal data augmentation
OCR2SEQ represents an innovative advancement in Optical Character Recognition (OCR)
technology, leveraging a multi-modal generative augmentation strategy to overcome …
technology, leveraging a multi-modal generative augmentation strategy to overcome …
Retrieve-and-Rank End-to-End Summarization of Biomedical Studies
An arduous biomedical task involves condensing evidence derived from multiple
interrelated studies, given a context as input, to generate reviews or provide answers …
interrelated studies, given a context as input, to generate reviews or provide answers …
Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials
Abstract Background Systematic reviews of Randomized Controlled Trials (RCTs) are an
important part of the evidence-based medicine paradigm. However, the creation of such …
important part of the evidence-based medicine paradigm. However, the creation of such …
ADAPTIVE IE: Investigating the Complementarity of Human-AI Collaboration to Adaptively Extract Information on-the-fly
Abstract Information extraction (IE) needs vary over time, where a flexible information
extraction (IE) system can be useful. Despite this, existing IE systems are either fully …
extraction (IE) system can be useful. Despite this, existing IE systems are either fully …
A Knowledge-Enhanced Hierarchical Reinforcement Learning-Based Dialogue System for Automatic Disease Diagnosis
Y Zhu, Y Li, Y Cui, T Zhang, D Wang, Y Zhang, S Feng - Electronics, 2023 - mdpi.com
Deep Reinforcement Learning is a key technology for the diagnosis-oriented medical
dialogue system, determining the type of disease according to the patient's utterances. The …
dialogue system, determining the type of disease according to the patient's utterances. The …
InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction
I Mondal, M Yuan, A Garimella, F Ferraro… - ar** Review of Datasets and Models
Background Question answering (QA) systems for patient-related data can assist both
clinicians and patients. They can, for example, assist clinicians in decision-making and …
clinicians and patients. They can, for example, assist clinicians in decision-making and …
Intra-template entity compatibility based slot-filling for clinical trial information extraction
C Witte, P Cimiano - Proceedings of the 21st Workshop on …, 2022 - aclanthology.org
We present a deep learning based information extraction system that can extract the design
and results of a published abstract describing a Randomized Controlled Trial (RCT). In …
and results of a published abstract describing a Randomized Controlled Trial (RCT). In …