Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Elke Rundensteiner"'
Autor:
Harriet Sibitenda, Awa Diattara, Assitan Traore, Ruofan Hu, Dongyu Zhang, Elke Rundensteiner, Cheikh Ba
Publikováno v:
IEEE Access, Vol 12, Pp 142343-142359 (2024)
The extraction of knowledge about prevalent issues discussed on social media in Africa using Artificial Intelligence techniques is vital for informing public governance. The objectives of our study are twofold: (a) to develop machine learning-based m
Externí odkaz:
https://doaj.org/article/6899c4a1d61f4678aab69db737666422
Autor:
Hamid Mansoor, Walter Gerych, Abdulaziz Alajaji, Luke Buquicchio, Kavin Chandrasekaran, Emmanuel Agu, Elke Rundensteiner, Angela Incollingo Rodriguez
Publikováno v:
Visual Informatics, Vol 7, Iss 2, Pp 13-29 (2023)
Digital phenotyping is the characterization of human behavior patterns based on data from digital devices such as smartphones in order to gain insights into the users’ state and especially to identify ailments. To support supervised machine learnin
Externí odkaz:
https://doaj.org/article/7e3973d0c30e44f0a51747b42c9ef0f4
Publikováno v:
Foods, Vol 12, Iss 20, p 3825 (2023)
Diseases caused by the consumption of food are a significant but avoidable public health issue, and identifying the source of contamination is a key step in an outbreak investigation to prevent foodborne illnesses. Historical foodborne outbreaks prov
Externí odkaz:
https://doaj.org/article/24adb0e22a36469895d131c61fb78c41
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Foodborne outbreaks are a serious but preventable threat to public health that often lead to illness, loss of life, significant economic loss, and the erosion of consumer confidence. Understanding how consumers respond when interacting with
Externí odkaz:
https://doaj.org/article/687c6d57923345e88d848bcfb42e1505
Autor:
Hamid Mansoor, Walter Gerych, Abdulaziz Alajaji, Luke Buquicchio, Kavin Chandrasekaran, Emmanuel Agu, Elke Rundensteiner
Publikováno v:
Visual Informatics, Vol 5, Iss 3, Pp 39-53 (2021)
Human Bio-Behavioral Rhythms (HBRs) such as sleep-wake cycles (Circadian Rhythms), and the degree of regularity of sleep and physical activity have important health ramifications. Ubiquitous devices such as smartphones can sense HBRs by continuously
Externí odkaz:
https://doaj.org/article/f83daaf599454f3e9241f1b564042ba7
Autor:
M.L. Tlachac, Miranda Reisch, Brittany Lewis, Ricardo Flores, Lane Harrison, Elke Rundensteiner
Publikováno v:
Healthcare Analytics, Vol 2, Iss , Pp 100088- (2022)
Mental illness screening instruments are increasingly being administered through online patient portals, making it vital to understand how the design of digital screening technologies could alter screening scores. Given the strong cross-cultural beli
Externí odkaz:
https://doaj.org/article/4e2c6be2927c48f79b256630aa757ced
Autor:
Dandan Tao, Ruofan Hu, Dongyu Zhang, Jasmine Laber, Anne Lapsley, Timothy Kwan, Liam Rathke, Elke Rundensteiner, Hao Feng
Publikováno v:
Foods, Vol 12, Iss 14, p 2769 (2023)
Foodborne diseases and outbreaks are significant threats to public health, resulting in millions of illnesses and deaths worldwide each year. Traditional foodborne disease surveillance systems rely on data from healthcare facilities, laboratories, an
Externí odkaz:
https://doaj.org/article/a8b7c37109ec4c80a12c4e232269002f
Autor:
Abdulaziz Alajaji, Walter Gerych, Luke Buquicchio, Kavin Chandrasekaran, Hamid Mansoor, Emmanuel Agu, Elke Rundensteiner
Publikováno v:
Sensors, Vol 23, Iss 6, p 3081 (2023)
Human context recognition (HCR) using sensor data is a crucial task in Context-Aware (CA) applications in domains such as healthcare and security. Supervised machine learning HCR models are trained using smartphone HCR datasets that are scripted or g
Externí odkaz:
https://doaj.org/article/533c96b7dded4e0eaac2859596dc87ad
Autor:
Edwin D. Boudreaux, Elke Rundensteiner, Feifan Liu, Bo Wang, Celine Larkin, Emmanuel Agu, Samiran Ghosh, Joshua Semeter, Gregory Simon, Rachel E. Davis-Martin
Publikováno v:
Frontiers in Psychiatry, Vol 12 (2021)
Objective: Early identification of individuals who are at risk for suicide is crucial in supporting suicide prevention. Machine learning is emerging as a promising approach to support this objective. Machine learning is broadly defined as a set of ma
Externí odkaz:
https://doaj.org/article/01d26ceec94444d8b4c6876a70f086b0
Autor:
Dennis Hofmann, Peter VanNostrand, Huayi Zhang, Yizhou Yan, Lei Cao, Samuel Madden, Elke Rundensteiner
Publikováno v:
Proceedings of the VLDB Endowment. 15:3706-3709
Anomaly detection is a critical task in applications like preventing financial fraud, system malfunctions, and cybersecurity attacks. While previous research has offered a plethora of anomaly detection algorithms, effective anomaly detection remains
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13f632718ad9aeea221ff42edb9b8f8b
https://doi.org/10.14778/3554821.3554880
https://doi.org/10.14778/3554821.3554880