Robotics & Machine Learning Daily News2024,Issue(MAY.16) :64-65.

University of Santo Tomas Reports Findings in Machine Learning (Spatiotemporal m odels of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning)

Robotics & Machine Learning Daily News2024,Issue(MAY.16) :64-65.

University of Santo Tomas Reports Findings in Machine Learning (Spatiotemporal m odels of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Manila, Phil ippines, by NewsRx correspondents, research stated, “Previous dengue epidemiolog ical analyses have been limited in spatiotemporal extent or covariate dimensions , the latter neglecting the multifactorial nature of dengue. These constraints, caused by rigid and traditional statistical tools which collapse amidst ‘Big Dat a’, prompt interpretable machine-learning (iML) approaches.”

Key words

Manila/Philippines/Asia/Cyborgs/Emer ging Technologies/Epidemiology/Health and Medicine/Machine Learning/Remote S ensing

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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