Machine learning in handling disease outbreaks: a comprehensive review
The changes in the global environment have made impact on the evolution of infectious
diseases, virus mutations, or new diseases which are challenging to be tackled with new …
diseases, virus mutations, or new diseases which are challenging to be tackled with new …
Twitter-aided decision making: a review of recent developments
Twitter is one of the largest online platforms where people exchange information. In the first
few years since its emergence, researchers have been exploring ways to use Twitter data in …
few years since its emergence, researchers have been exploring ways to use Twitter data in …
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 …
Detection of COVID-19 epidemic outbreak using machine learning
Background The coronavirus disease (COVID-19) pandemic has spread rapidly across the
world, creating an urgent need for predictive models that can help healthcare providers …
world, creating an urgent need for predictive models that can help healthcare providers …
[PDF][PDF] Drug sentiment analysis using machine learning classifiers
In recent times, one of the most emerging sub-dimensions of natural language processing is
sentiment analysis which refers to analyzing opinion on a particular subject from plain text …
sentiment analysis which refers to analyzing opinion on a particular subject from plain text …
[HTML][HTML] Use of Digital Tools in Arbovirus Surveillance: Sco** Review
CL Melo, LR Mageste, L Guaraldo, DP Paula… - Journal of Medical …, 2024 - jmir.org
Background The development of technology and information systems has led to important
changes in public health surveillance. Objective This sco** review aimed to assess the …
changes in public health surveillance. Objective This sco** review aimed to assess the …
Hybrid Machine Learning Approach to Zero-Inflated Data Improves Accuracy of Dengue Prediction
Background Spatiotemporal dengue forecasting using machine learning (ML) can contribute
to the development of prevention and control strategies for impending dengue outbreaks …
to the development of prevention and control strategies for impending dengue outbreaks …
[PDF][PDF] Comparison of naïve bayes algorithm and XGBoost on local product review text classification
Online reviews are critical in supporting purchasing decisions because, with the
development of ecommerce, there are more and more fake reviews, so more and more …
development of ecommerce, there are more and more fake reviews, so more and more …
Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer
This research delves into the obstacles and difficulties associated with predicting
cryptocurrency movements in the volatile global financial market. This study develops and …
cryptocurrency movements in the volatile global financial market. This study develops and …
Machine learning in infectious diseases: potential applications and limitations
Infectious diseases are a major threat for human and animal health worldwide. Artificial
Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics …
Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics …