Pre-trained language models in biomedical domain: A systematic survey
Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …
language processing tasks. This also benefits the biomedical domain: researchers from …
[HTML][HTML] AMMU: a survey of transformer-based biomedical pretrained language models
KS Kalyan, A Rajasekharan, S Sangeetha - Journal of biomedical …, 2022 - Elsevier
Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …
natural language processing (NLP). These models combine the power of transformers …
CancerBERT: a cancer domain-specific language model for extracting breast cancer phenotypes from electronic health records
Objective Accurate extraction of breast cancer patients' phenotypes is important for clinical
decision support and clinical research. This study developed and evaluated cancer domain …
decision support and clinical research. This study developed and evaluated cancer domain …
A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics
The utilization of large language models (LLMs) in the Healthcare domain has generated
both excitement and concern due to their ability to effectively respond to freetext queries with …
both excitement and concern due to their ability to effectively respond to freetext queries with …
A survey on semantic processing techniques
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …
era of powerful pre-trained language models and large language models, the advancement …
Contextualized medication information extraction using transformer-based deep learning architectures
Objective To develop a natural language processing (NLP) system to extract medications
and contextual information that help understand drug changes. This project is part of the …
and contextual information that help understand drug changes. This project is part of the …
Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing
Objective Seizure frequency and seizure freedom are among the most important outcome
measures for patients with epilepsy. In this study, we aimed to automatically extract this …
measures for patients with epilepsy. In this study, we aimed to automatically extract this …
Clinical concept and relation extraction using prompt-based machine reading comprehension
Objective To develop a natural language processing system that solves both clinical concept
extraction and relation extraction in a unified prompt-based machine reading …
extraction and relation extraction in a unified prompt-based machine reading …
Artificial Immune Cell, AI‐cell, a New Tool to Predict Interferon Production by Peripheral Blood Monocytes in Response to Nucleic Acid Nanoparticles
M Chandler, S Jain, J Halman, E Hong… - Small, 2022 - Wiley Online Library
Nucleic acid nanoparticles, or NANPs, rationally designed to communicate with the human
immune system, can offer innovative therapeutic strategies to overcome the limitations of …
immune system, can offer innovative therapeutic strategies to overcome the limitations of …
Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review
Abstract Background Natural Language Processing (NLP) applications have developed
over the past years in various fields including its application to clinical free text for named …
over the past years in various fields including its application to clinical free text for named …