Researcher Search Results >> Anno Sumiko

Anno Sumiko

Name	Anno Sumiko
Affiliation	Sophia University
Section	Graduate School of Global Environmental Studies, Master's (Doctoral) Program in Global Environmental Studies
Job title	Professor
Degree	修士（公衆衛生学）(ニューヨーク医科大学), 博士（医学）(神戸大学)
Other Affiliation	Sophia University（Concurrent positions） Applied Data Science Degree Program
Research funding number	10333527
J-Global ID	201001083389571077

Profile

Applied research on health effects due to climate change using remote sensing, GIS, machine learning, and deep learning
(Subject of research) Applied research on health effects using remote sensing, GIS, machine learning, and deep learning

Research Interests

Machine Learning, Deep Learning, Spatial Information Science, Remote Sensing

Research Areas

Life sciences / Hygiene and public health (non-laboratory) /
Life sciences / Hygiene and public health (laboratory) /

Awards

Oct 2009

Best Presentation,Brunei Darussalam

Jan 2009

宮地杭一記念賞

Jun 2008

2007年度日本生理人類学会優秀論文賞

Papers

12 3 4 5 >

Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning

Sumiko Anno Hirakawa Tsubasa Satoru Sugita Shinya Yasumoto Ming-An Lee Yoshinobu Sasaki Kei Oyoshi

Geo-spatial Information Science DOI: 10.1080/10095020.2022.2144770 Jan 2023 [Refereed]

Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon

Awah Rita Engwari Sumiko Anno Ako Andrew

The 37th Congress of Japan Association for International Health 92 Oct 2022 [Refereed]

A graph convolutional network for predicting COVID-19 dynamics in 190 regions/countries

Sumiko Anno Tsubasa Hirakawa Satoru Sugita Shinya Yasumoto

Frontiers in Public Health 10:911336. doi: 10.3389/fpubh.2022. Aug 2022 [Refereed]

Introduction:

Coronavirus disease (COVID-19) rapidly spread from Wuhan, China to other parts of China and other regions/countries around the world, resulting in a pandemic due to large populations moving through the massive transport hubs connect...

Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning

Sumiko Anno Takeshi Hara Hiroki Kai Ming-An Lee Yi Chang Kei Oyoshi Yousei Mizukami Takeo Tadono

Geospatial Health 14(2) 183-194 Nov 2019 [Refereed]

Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is endemic. A vaccine is not available and has yet to reach the market due to the economic burden o...

Predicting Spatiotemporal Distribution of Dengue Fever in Taiwan Using Deep Learning

Sumiko Anno Kazuhiro Yamasaki Ming-An Lee Yi Chang Hiroki Kai Kei Oyoshi Yosei Mizukami Takeo Tadono

The 32nd International Symposium on Space Technology and Science (ISTS) & the 9th Nano-Satellite Symposium (NSAT) 1-3 Jun 2019 [Refereed]