Cargando…
A Light-Weight Text Summarization System for Fast Access to Medical Evidence
As the volume of published medical research continues to grow rapidly, staying up-to-date with the best-available research evidence regarding specific topics is becoming an increasingly challenging problem for medical experts and researchers. The current COVID19 pandemic is a good example of a topic...
Autores principales: | Sarker, Abeed, Yang, Yuan-Chi, Al-Garadi, Mohammed Ali, Abbas, Aamir |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521877/ https://www.ncbi.nlm.nih.gov/pubmed/34713057 http://dx.doi.org/10.3389/fdgth.2020.585559 |
Ejemplares similares
-
Comparison of Pretraining Models and Strategies for Health-Related Social Media Text Classification
por: Guo, Yuting, et al.
Publicado: (2022) -
The Early Detection of Fraudulent COVID-19 Products From Twitter Chatter: Data Set and Baseline Approach Using Anomaly Detection
por: Sarker, Abeed, et al.
Publicado: (2023) -
Leveraging the potential of synthetic text for AI in mental healthcare
por: Ive, Julia
Publicado: (2022) -
Text classification models for the automatic detection of nonmedical prescription medication use from social media
por: Al-Garadi, Mohammed Ali, et al.
Publicado: (2021) -
Effects of Negation and Uncertainty Stratification on Text-Derived Patient Profile Similarity
por: Slater, Luke T., et al.
Publicado: (2021)