Sumiko Anno, Hirakawa Tsubasa, Satoru Sugita, Shinya Yasumoto, Ming-An Lee, Yoshinobu Sasaki, Kei Oyoshi. Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning. Geo-spatial Information Science. 2023. DOI: 10.1080/10095020.2022.2144770
Awah Rita Engwari, Sumiko Anno, Ako Andrew. Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon. The 37th Congress of Japan Association for International Health. 2022. 92
Sumiko Anno, Tsubasa Hirakawa, Satoru Sugita, Shinya Yasumoto. A graph convolutional network for predicting COVID-19 dynamics in 190 regions/countries. Frontiers in Public Health. 2022. 10:911336. doi: 10.3389/fpubh.2022
Sumiko Anno, Takeshi Hara, Hiroki Kai, Ming-An Lee, Yi Chang, Kei Oyoshi, Yousei Mizukami, Takeo Tadono. Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning. Geospatial Health. 2019. 14. 2. 183-194
Sumiko Anno, Kazuhiro Yamasaki, Ming-An Lee, Yi Chang, Hiroki Kai, Kei Oyoshi, Yosei Mizukami, Takeo Tadono. Predicting Spatiotemporal Distribution of Dengue Fever in Taiwan Using Deep Learning. The 32nd International Symposium on Space Technology and Science (ISTS) & the 9th Nano-Satellite Symposium (NSAT). 2019. 1-3
Challenges of predicting the spatiotemporal distribution of dengue fever outbreak using remote sensing data and deep learning
(The International Conference on Geospatial Information Science - Education, Innovation and Applications 2023 2023)
Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon
(The 37th Congress of Japan Association for International Health 2022)