Risk prediction system for dengue transmission based on high resolution weather data.

Autor: Chathurika Hettiarachchige, Stefan von Cavallar, Timothy Lynar, Roslyn I Hickson, Manoj Gambhir

Publikováno v: PLoS ONE, Vol 13, Iss 12, p e0208203 (2018)

BackgroundDengue is the fastest spreading vector-borne viral disease, resulting in an estimated 390 million infections annually. Precise prediction of many attributes related to dengue is still a challenge due to the complex dynamics of the disease.

Externí odkaz: https://doaj.org/article/9a1c3bafb2494fc29394dacadf773a14

Contributors

Autor: Umer Akbar, Ali Akbari, Parastoo Alinia, Francesco Amato, Sara Amendola, Ertan Balaban, Christopher Beach, Mattia Bertschi, Fabian Braun, Laura Caldani, Francesca Camera, Alexander J. Casson, Gert Cauwenberghs, Gozde Cay, Yu M. Chi, Nicholas Constant, Marco Di Rienzo, Xiaorong Ding, Rassoul Diouf, Muhammad Farooq, Timothy Fazio, Damien Ferrario, Juan Manuel Fontana, Todd J. Freeborn, Elsa Genzoni, Hassan Ghasemzadeh, Maysam Ghovanloo, Sohmyung Ha, Stefan Harrer, Roozbeh Jafari, Sundaresan Jayaraman, Yuqi Jiang, Panagiotis Kassanos, Meysam Keshavarz, Chul Kim, Amanda Koh, Ilkka Korhonen, Yuichi Kurita, Tomohiro Kuroda, Mathieu Lemay, Steffen Leonhardt, Markus Lüken, Ningqi Luo, Kunal Mankodiya, Andre L. Mansano, Gaetano Marrocco, Gustavo C. Martins, Atsuji Masuda, Patrick P. Mercier, Carolina Miozzi, Mahtab Mirmomeni, Jens Mühlsteff, Simone Nappi, Cecilia Occhiuzzi, Rita Paradiso, Jakub Parak, Sungmee Park, Nicolai Petkov, Sara Piccirillo, Carmen C.Y. Poon, Martin Proença, Petia Radeva, Vignesh Ravichandran, Philippe Renevey, Bruno Gil Rosa, Edward Sazonov, Wouter A. Serdijn, Josep Sola, Mark Stoopman, Hideya Takahashi, Estefania Talavera, Mark Ulbrich, Vishesh Vikas, Stefan von Cavallar, Hui Wang, Guang-Zhong Yang, Yuan Ting Zhang, Yali Zheng

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1fbbaee43814e3c1249901870bb49472
https://doi.org/10.1016/b978-0-12-819246-7.09990-3

Towards Automated and Marker-less Parkinson Disease Assessment: Predicting UPDRS Scores using Sit-stand videos

Autor: Jeffrey Rogers, Tian Hao, Deval Mehta, Umar Asif, Stefan Harrer, Stefan von Cavallar, Erhan Bilal

Publikováno v: CVPR Workshops

This paper presents a novel deep learning enabled, video based analysis framework for assessing the Unified Parkinsons Disease Rating Scale (UPDRS) that can be used in the clinic or at home. We report results from comparing the performance of the fra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0963cfb9a2f4eeacb53fab5dd8cd02b7

A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition

Autor: Mani, Abedini, Stefan, von Cavallar, Rajib, Chakravorty, Matthew, Davis, Rahil, Garnavi

Publikováno v: Studies in health technology and informatics. 216

Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are driving the creation of new and innovative health diagnostic applications. We describe a service and application for performing image training and rec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::df01bb3d1972074f5fa7ae5f1a81fb48
https://pubmed.ncbi.nlm.nih.gov/26262140