Deep learning for health informatics

D Ravì, C Wong, F Deligianni… - IEEE journal of …, 2016 - ieeexplore.ieee.org
With a massive influx of multimodality data, the role of data analytics in health informatics
has grown rapidly in the last decade. This has also prompted increasing interests in the …

[HTML][HTML] Social media based surveillance systems for healthcare using machine learning: a systematic review

A Gupta, R Katarya - Journal of biomedical informatics, 2020 - Elsevier
Background Real-time surveillance in the field of health informatics has emerged as a
growing domain of interest among worldwide researchers. Evolution in this field has helped …

A survey on deep learning for big data

Q Zhang, LT Yang, Z Chen, P Li - Information Fusion, 2018 - Elsevier
Deep learning, as one of the most currently remarkable machine learning techniques, has
achieved great success in many applications such as image analysis, speech recognition …

Collaborative city digital twin for the COVID-19 pandemic: A federated learning solution

J Pang, Y Huang, Z ** behavior during COVID-19 pandemic: A Bangladeshi consumers' perspectives
MR Miah, A Hossain, R Shikder, T Saha, M Neger - Heliyon, 2022 - cell.com
Background of the study Nowadays, the business pattern is changing globally. The business
organization is influenced customers to purchase their necessary goods and services from …

Deep learning in the biomedical applications: Recent and future status

R Zemouri, N Zerhouni, D Racoceanu - Applied Sciences, 2019 - mdpi.com
Deep neural networks represent, nowadays, the most effective machine learning technology
in biomedical domain. In this domain, the different areas of interest concern the Omics (study …

A sco** review of the use of Twitter for public health research

O Edo-Osagie, B De La Iglesia, I Lake… - Computers in biology and …, 2020 - Elsevier
Public health practitioners and researchers have used traditional medical databases to
study and understand public health for a long time. Recently, social media data, particularly …

Sosnet: A graph convolutional network approach to fine-grained cyberbullying detection

J Wang, K Fu, CT Lu - … Conference on Big Data (Big Data), 2020 - ieeexplore.ieee.org
Amidst the COVID-19 pandemic, cyberbullying has become an even more serious threat.
Our work aims to investigate the viability of an automatic multiclass cyberbullying detection …

RETRACTED ARTICLE: Recent Deep Learning Techniques, Challenges and Its Applications for Medical Healthcare System: A Review

SK Pandey, RR Janghel - Neural Processing Letters, 2019 - Springer
The concept of deep learning originates from artificial neural networks which has become a
very popular research area during the past few decades. There are two main reasons for for …