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

Anno, Sumiko ; Hirakawa, Tsubasa ; Sugita, Satoru ; Yasumoto, Shinya

Frontiers in public health, 2022-08, Vol.10, p.911336-911336 [Periódico revisado por pares]

Frontiers Media S.A

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2
Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning
Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning
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Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning

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

Geospatial health, 2019-11, Vol.14 (2) [Periódico revisado por pares]

Italy: PAGEPress Publications

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3
Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning
Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning
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Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning

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

Geo-spatial information science, 2023-01, Vol.ahead-of-print (ahead-of-print), p.1-7 [Periódico revisado por pares]

Taylor & Francis

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4
Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka
Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka
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Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

Anno, Sumiko ; Imaoka, Keiji ; Tadono, Takeo ; Igarashi, Tamotsu ; Sivaganesh, Subramaniam ; Kannathasan, Selvam ; Kumaran, Vaithehi ; Surendran, Sinnathamby Noble

Geospatial health, 2015-11, Vol.10 (2), p.376-376 [Periódico revisado por pares]

Italy: PAGEPress Publications

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5
Interactions between SNP alleles at multiple loci contribute to skin color differences between caucasoid and mongoloid subjects
Interactions between SNP alleles at multiple loci contribute to skin color differences between caucasoid and mongoloid subjects
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Interactions between SNP alleles at multiple loci contribute to skin color differences between caucasoid and mongoloid subjects

Anno, Sumiko ; Abe, Takashi ; Yamamoto, Takushi

International journal of biological sciences, 2008-03, Vol.4 (2), p.81-86 [Periódico revisado por pares]

Australia: Ivyspring International Publisher

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6
EO4-5. Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon
EO4-5. Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon
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EO4-5. Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon

Awah Rita ; Sumiko Anno ; Ako Andrew

Journal of International Health, 2023, Vol.38 (3), p.135-135

Japan Association for International Health

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7
Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning
Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning
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Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning

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

Taylor & Francis 2023

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8
MC1R variants increased the risk of sporadic cutaneous melanoma in darker‐pigmented Caucasians: A pooled‐analysis from the M‐SKIP project
MC1R variants increased the risk of sporadic cutaneous melanoma in darker‐pigmented Caucasians: A pooled‐analysis from the M‐SKIP project
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MC1R variants increased the risk of sporadic cutaneous melanoma in darker‐pigmented Caucasians: A pooled‐analysis from the M‐SKIP project

Pasquali, Elena ; García‐Borrón, José C. ; Fargnoli, Maria Concetta ; Gandini, Sara ; Maisonneuve, Patrick ; Bagnardi, Vincenzo ; Specchia, Claudia ; Liu, Fan ; Kayser, Manfred ; Nijsten, Tamar ; Nagore, Eduardo ; Kumar, Rajiv ; Hansson, Johan ; Kanetsky, Peter A. ; Ghiorzo, Paola ; Debniak, Tadeusz ; Branicki, Wojciech ; Gruis, Nelleke A. ; Han, Jiali ; Dwyer, Terry ; Blizzard, Leigh ; Landi, Maria Teresa ; Palmieri, Giuseppe ; Ribas, Gloria ; Stratigos, Alexander ; Council, M. Laurin ; Autier, Philippe ; Little, Julian ; Newton‐Bishop, Julia ; Sera, Francesco ; Raimondi, Sara

International journal of cancer, 2015-02, Vol.136 (3), p.618-631 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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9
MC1R gene variants and non-melanoma skin cancer: a pooled-analysis from the M-SKIP project
MC1R gene variants and non-melanoma skin cancer: a pooled-analysis from the M-SKIP project
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MC1R gene variants and non-melanoma skin cancer: a pooled-analysis from the M-SKIP project

Tagliabue, E ; Fargnoli, M C ; Gandini, S ; Maisonneuve, P ; Liu, F ; Kayser, M ; Nijsten, T ; Han, J ; Kumar, R ; Gruis, N A ; Ferrucci, L ; Branicki, W ; Dwyer, T ; Blizzard, L ; Helsing, P ; Autier, P ; García-Borrón, J C ; Kanetsky, P A ; Landi, M T ; Little, J ; Newton-Bishop, J ; Sera, F ; Raimondi, S

Breast cancer research and treatment, 2015-07, Vol.113 (2), p.354-363 [Periódico revisado por pares]

England: Nature Publishing Group

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10
Approaches to understanding adaptations of skin color variation by detecting gene-environment interactions
Approaches to understanding adaptations of skin color variation by detecting gene-environment interactions
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Approaches to understanding adaptations of skin color variation by detecting gene-environment interactions

Anno, Sumiko ; Ohshima, Kazuhiko ; Abe, Takashi

Expert review of molecular diagnostics, 2010-11, Vol.10 (8), p.987-991 [Periódico revisado por pares]

England: Taylor & Francis

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