Early Stage Machine Learning-Based Prediction of US County Vulnerability to the COVID-19 Pandemic: Machine Learning Approach
BackgroundThe rapid spread of COVID-19 means that government and health services providers have little time to plan and design effective response policies. It is therefore important to quickly provide accurate predictions of how vulnerable geographic regions such as counties are to the spread of thi...
Saved in:
Main Authors: | Mehta, Mihir (Author), Julaiti, Juxihong (Author), Griffin, Paul (Author), Kumara, Soundar (Author) |
---|---|
Format: | Book |
Published: |
JMIR Publications,
2020-09-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning-Based Approach
by: Queena Cheong, et al.
Published: (2021) -
Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models
by: C. Kavitha, et al.
Published: (2022) -
Machine learning‐directed electrical impedance tomography to predict metabolically vulnerable plaques
by: Justin Chen, et al.
Published: (2024) -
The application of machine learning for predicting recurrence in patients with early-stage endometrial cancer: a pilot study
by: Munetoshi Akazawa, et al.
Published: (2021) -
The early prediction of gestational diabetes mellitus by machine learning models
by: Yeliz Kaya, et al.
Published: (2024)