Deep learning techniques on text classification using Natural language processing (NLP) in social healthcare network: A comprehensive survey
PM Lavanya, E Sasikala - 2021 3rd international conference …, 2021 - ieeexplore.ieee.org
The social media is becoming an increasing trend for sharing the thoughts, ideas, opinions,
etc. based on online reviews which generates a tremendous amount of unstructured data …
etc. based on online reviews which generates a tremendous amount of unstructured data …
Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review
E Sylvestre, C Joachim, E Cecilia-Joseph… - PLoS neglected …, 2022 - journals.plos.org
Background Traditionally, dengue surveillance is based on case reporting to a central health
agency. However, the delay between a case and its notification can limit the system …
agency. However, the delay between a case and its notification can limit the system …
A robust heart disease prediction system using hybrid deep neural networks
Heart Disease (HD) is recognized as the leading cause of worldwide mortality by the World
Health Organization (WHO), resulting in the loss of approximately 17.9 million lives each …
Health Organization (WHO), resulting in the loss of approximately 17.9 million lives each …
Big data directed acyclic graph model for real-time COVID-19 twitter stream detection
Every day, large-scale data are continuously generated on social media as streams, such as
Twitter, which inform us about all events around the world in real-time. Notably, Twitter is …
Twitter, which inform us about all events around the world in real-time. Notably, Twitter is …
Smart policing technique with crime type and risk score prediction based on machine learning for early awareness of risk situation
MS Baek, W Park, J Park, KH Jang, YT Lee - IEEE Access, 2021 - ieeexplore.ieee.org
In order to quickly and effectively respond to a newly received criminal case, information
regarding the type and severity of the case is crucial for authorities. This paper designs and …
regarding the type and severity of the case is crucial for authorities. This paper designs and …
A GPT-based EHR modeling system for unsupervised novel disease detection
Abstract Objective To develop an Artificial Intelligence (AI)-based anomaly detection model
as a complement of an “astute physician” in detecting novel disease cases in a hospital and …
as a complement of an “astute physician” in detecting novel disease cases in a hospital and …
Adapting recurrent neural networks for classifying public discourse on COVID-19 symptoms in Twitter content
The COVID-19 infection, which began in December 2019, has claimed many lives and
impacted all aspects of human life. With time, COVID-19 was identified as a pandemic …
impacted all aspects of human life. With time, COVID-19 was identified as a pandemic …
Optimal policy learning for COVID-19 prevention using reinforcement learning
MI Uddin, SA Ali Shah… - Journal of …, 2022 - journals.sagepub.com
COVID-19 has changed the lifestyle of many people due to its rapid human-to-human
transmission. The spread started at the end of January 2020, and different countries used …
transmission. The spread started at the end of January 2020, and different countries used …
Deep learning techniques for detection and prediction of pandemic diseases: a systematic literature review
Deep learning (DL) is becoming a fast-growing field in the medical domain and it helps in
the timely detection of any infectious disease (IDs) and is essential to the management of …
the timely detection of any infectious disease (IDs) and is essential to the management of …
[PDF][PDF] Machine learning approach for COVID-19 detection on twitter
Social networking services (SNSs) provide massive data that can be a very influential
source of information during pandemic outbreaks. This study shows that social media …
source of information during pandemic outbreaks. This study shows that social media …