Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review

Response to COVID-19 in Taiwan

(2020) C. Jason Wang et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Pneumonia of unknown aetiology in Wuhan, China: potential for international spread via commercial air travel

(2020) Isaac I Bogoch et al.   JOURNAL OF TRAVEL MEDICINE

Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study

(2020) Joseph T Wu et al.   LANCET

Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak

(2020) Shi Zhao et al.   Journal of Clinical Medicine

Analysis of COVID-19 infection spread in Japan based on stochastic transition model

(2020) Kenji Karako et al.   BioScience Trends

Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

(2020) Joel R Koo et al.   LANCET INFECTIOUS DISEASES

Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles

(2019) Aldenor G. Santos et al.   Scientific Reports

Main factors influencing recovery in MERS Co-V patients using machine learning

(2019) Maya John et al.   Journal of Infection and Public Health

A dynamic neural network model for predicting risk of Zika in real time

(2019) Mahmood Akhtar et al.   BMC Medicine

An open challenge to advance probabilistic forecasting for dengue epidemics

(2019) Michael A. Johansson et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Mapping the transmission risk of Zika virus using machine learning models

(2018) Dong Jiang et al.   ACTA TROPICA

Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model

(2018) Sebastian Funk et al.   Epidemics

In situ immune response and mechanisms of cell damage in central nervous system of fatal cases microcephaly by Zika virus

(2018) Raimunda S. S. Azevedo et al.   Scientific Reports

Predicting Infectious Disease Using Deep Learning and Big Data

(2018) Sangwon Chae et al.   International Journal of Environmental Research and Public Health

Digital Phenotyping

(2017) Thomas R. Insel   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

An unsupervised machine learning model for discovering latent infectious diseases using social media data

(2017) Sunghoon Lim et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks

(2017) Sungwoon Choi et al.   METHODS

Dynamic Forecasting of Zika Epidemics Using Google Trends

(2017) Yue Teng et al.   PLoS One

Using online social networks to track a pandemic: A systematic review

(2016) Mohammed Ali Al-garadi et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health

(2016) Jukka-Pekka Onnela et al.   NEUROPSYCHOPHARMACOLOGY

Developing Global Norms for Sharing Data and Results during Public Health Emergencies

(2016) Kayvon Modjarrad et al.   PLOS MEDICINE

Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients

(2016) Andres Colubri et al.   PLoS Neglected Tropical Diseases

Infectious Disease Modeling Methods as Tools for Informing Response to Novel Influenza Viruses of Unknown Pandemic Potential

(2015) Manoj Gambhir et al.   CLINICAL INFECTIOUS DISEASES

Using Results From Infectious Disease Modeling to Improve the Response to a Potential H7N9 Influenza Pandemic

(2015) Sonja A. Rasmussen et al.   CLINICAL INFECTIOUS DISEASES

The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

(2015) Peng Zhang et al.   Computational Intelligence and Neuroscience

Global trends in emerging infectious diseases

(2008) Kate E. Jones et al.   NATURE