A personalized respiratory disease exacerbation prediction technique based on a novel spatio-temporal machine learning architecture and local environmental sensor networks

HIGHLIGHTS

• who: Rohan T. Bhowmik and Sam P. Most from the School of Medicine, Stanford University, Stanford, CA, USA have published the article: A Personalized Respiratory Disease Exacerbation Prediction Technique Based on a Novel Spatio-Temporal Machine Learning Architecture and Local Environmental Sensor Networks, in the Journal: Electronics 2022, 11, 2562. of /2022/
• what: The aim of this research is to develop an early-warning system based on AI and multi-factor analysis to reduce hospitalizations and medical costs, and demonstrate the feasibility of deploying a passive, continuous, remote patient monitoring and telehealth solution for chronic . . .
  

   

  

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