Natural language processing for smart healthcare

B Zhou, G Yang, Z Shi, S Ma - IEEE Reviews in Biomedical …, 2022 - ieeexplore.ieee.org
Smart healthcare has achieved significant progress in recent years. Emerging artificial
intelligence (AI) technologies enable various smart applications across various healthcare …

Efficient automated processing of the unstructured documents using artificial intelligence: A systematic literature review and future directions

D Baviskar, S Ahirrao, V Potdar, K Kotecha - IEEE Access, 2021 - ieeexplore.ieee.org
The unstructured data impacts 95% of the organizations and costs them millions of dollars
annually. If managed well, it can significantly improve business productivity. The traditional …

A modern approach towards an industry 4.0 model: From driving technologies to management

G Tsaramirsis, A Kantaros, I Al-Darraji… - Journal of …, 2022 - Wiley Online Library
Every so often, a confluence of novel technologies emerges that radically transforms every
aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of …

Universalner: Targeted distillation from large language models for open named entity recognition

W Zhou, S Zhang, Y Gu, M Chen, H Poon - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable generalizability, such as
understanding arbitrary entities and relations. Instruction tuning has proven effective for …

Constructing a disease database and using natural language processing to capture and standardize free text clinical information

S Raza, B Schwartz - Scientific Reports, 2023 - nature.com
The ability to extract critical information about an infectious disease in a timely manner is
critical for population health research. The lack of procedures for mining large amounts of …

Transforming epilepsy research: A systematic review on natural language processing applications

ANJ Yew, M Schraagen, WM Otte, E van Diessen - Epilepsia, 2023 - Wiley Online Library
Despite improved ancillary investigations in epilepsy care, patients' narratives remain
indispensable for diagnosing and treatment monitoring. This wealth of information is …

Large-scale application of named entity recognition to biomedicine and epidemiology

S Raza, DJ Reji, F Shajan, SR Bashir - PLOS Digital Health, 2022 - journals.plos.org
Background Despite significant advancements in biomedical named entity recognition
methods, the clinical application of these systems continues to face many challenges:(1) …

A survey on event extraction for natural language understanding: Riding the biomedical literature wave

G Frisoni, G Moro, A Carbonaro - IEEE Access, 2021 - ieeexplore.ieee.org
Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …

Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach

S Raza, B Schwartz - BMC Medical Informatics and Decision Making, 2023 - Springer
Background Extracting relevant information about infectious diseases is an essential task.
However, a significant obstacle in supporting public health research is the lack of methods …

TaxoNERD: deep neural models for the recognition of taxonomic entities in the ecological and evolutionary literature

N Le Guillarme, W Thuiller - Methods in Ecology and Evolution, 2022 - Wiley Online Library
Easy access to multi‐taxa information (eg distribution, traits, diet) in the scientific literature is
essential to understand, map and predict all‐inclusive biodiversity. Tools are needed to …