Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Alexandra Zytek"'
Autor:
Furui Cheng, Dongyu Liu, Huamin Qu, Yanna Lin, Alexandra Zytek, Fan Du, Haomin Li, Kalyan Veeramachaneni
Publikováno v:
IEEE transactions on visualization and computer graphics. 28(1)
Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model transparency and interpretability limit their adoption in clinical pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac736f3c9c71a556090635bb0486cbff
https://pubmed.ncbi.nlm.nih.gov/34596543
https://pubmed.ncbi.nlm.nih.gov/34596543
Publikováno v:
CHI Extended Abstracts
As machine learning is applied to an increasingly large number of domains, the need for an effective way to explain its predictions grows apace. In the domain of child welfare screening, machine learning offers a promising method of consolidating the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02876c8a823d114a2f20b3d2af7ce72d
https://doi.org/10.1145/3411763.3451743
https://doi.org/10.1145/3411763.3451743
Machine learning (ML) is being applied to a diverse and ever-growing set of domains. In many cases, domain experts - who often have no expertise in ML or data science - are asked to use ML predictions to make high-stakes decisions. Multiple ML usabil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c01ebd08e5efb1f584b5ddcfdd00e89
http://arxiv.org/abs/2103.02071
http://arxiv.org/abs/2103.02071
Detecting anomalies in time-varying multivariate data is crucial in various industries for the predictive maintenance of equipment. Numerous machine learning (ML) algorithms have been proposed to support automated anomaly identification. However, a s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a745988115d0428184d5d317945f066
Publikováno v:
2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2811816a0d7671f46a9291dad8b244a2
https://doi.org/10.1109/dasc.2018.8569842
https://doi.org/10.1109/dasc.2018.8569842
Autor:
Cheng, Furui, Liu, Dongyu, Du, Fan, Lin, Yanna, Zytek, Alexandra, Li, Haomin, Qu, Huamin, Veeramachaneni, Kalyan
Publikováno v:
IEEE Transactions on Visualization & Computer Graphics; Jan2022, Vol. 28 Issue 1, p378-388, 11p
Publikováno v:
IEEE Transactions on Visualization & Computer Graphics; Jan2022, Vol. 28 Issue 1, p1161-1171, 11p
Autor:
Imai, Shigeru, Blasch, Erik, Galli, Alessandro, Zhu, Wennan, Lee, Frederick, Varela, Carlos A.
Publikováno v:
IEEE Aerospace & Electronic Systems; Apr2017, Vol. 32 Issue 4, p4-17, 14p
Publikováno v:
IEEE Transactions on Visualization & Computer Graphics; Jan2022, Vol. 28 Issue 1, pii-xi, 1p
Autor:
Lee, Bongshin, Miksch, Silvia, Ynnerman, Anders, Bezerianos, Anastasia, Chen, Jian, Chen, Wei, Collins, Christopher, Gleicher, Michael, Groller, Eduard, Lex, Alexander, Preim, Bernhard, Seo, Jinwook, Westermann, Ruediger, Yang, Jing, Yuan, Xiaoru, Shen, Han-Wei, Fekete, Jean-Daniel, Liu, Shixia
Publikováno v:
IEEE Transactions on Visualization & Computer Graphics; Jan2022, Vol. 28 Issue 1, pxiv-xxiii, 1p