Machine learning models for preventative mobile health asthma control

As proved by the XGBoost model, predicting asthma triggers can be a viable option for asthma control using machine learning. In addition, the actionable information of triggers, allows patients to make behavior changes. However there will still need to be work testing the system in a mobile health system.

Authors

Institutions

Publication Details

Journal
Journal of Asthma
Published
2025-01-16
DOI
https://doi.org/10.1080/02770903.2025.2453812
Citations
2
Primary Topic
Asthma and respiratory diseases
Type
article
Field-Weighted Citation Impact
2.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Machine learning models for preventative mobile health asthma control

Alan S.L. Wong
2 citations
Journal of Asthma
Asthma and respiratory diseases
2.33
article

Machine learning models for preventative mobile health asthma control

Alan S.L. Wong
article en
2 citations

Abstract

As proved by the XGBoost model, predicting asthma triggers can be a viable option for asthma control using machine learning. In addition, the actionable information of triggers, allows patients to make behavior changes. However there will still need to be work testing the system in a mobile health system.

Journal of AsthmaVol. 62(6)
Wake Technical Community College (US)
Openalex Percentile: Top 15%
Asthma and respiratory diseases
2.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Machine learning models for preventative mobile health asthma control — Alan S.L. Wong · Journal of Asthma (2025) | TGRS Research Map | TGRS