Zobrazeno 1 - 10 of 7 099 pro vyhledávání: '"Erić K"'
1
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
2
Report
HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation
Autor: Acosta, Julián N., Zhang, Xiaoman, Dogra, Siddhant, Zhou, Hong-Yu, Payabvash, Seyedmehdi, Falcone, Guido J., Oermann, Eric K., Rajpurkar, Pranav
We present Head CT Ontology Normalized Evaluation (HeadCT-ONE), a metric for evaluating head CT report generation through ontology-normalized entity and relation extraction. HeadCT-ONE enhances current information extraction derived metrics (such as
Externí odkaz: http://arxiv.org/abs/2409.13038
Zobrazit plný text záznamu
5
Report
Cross-Relation Characterization of Knowledge Networks
Autor: Tokuda, Eric K., Lambiotte, Renaud, Costa, Luciano da F.
Knowledge networks have become increasingly important as a changing repository of data which can be represented, studied and modeled by using complex networks concepts and methodologies. Here we report a study of knowledge networks corresponding to t
Externí odkaz: http://arxiv.org/abs/2306.15741
Zobrazit plný text záznamu
6
Report
Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction
Autor: Yang, Grace, Cao, Ming, Jiang, Lavender Y., Liu, Xujin C., Cheung, Alexander T. M., Weiss, Hannah, Kurland, David, Cho, Kyunghyun, Oermann, Eric K.
Traditional evaluation metrics for classification in natural language processing such as accuracy and area under the curve fail to differentiate between models with different predictive behaviors despite their similar performance metrics. We introduc
Externí odkaz: http://arxiv.org/abs/2211.07047
Zobrazit plný text záznamu
7
Report
City Motifs as Revealed by Similarity Between Hierarchical Features
Autor: Domingues, Guilherme S., Tokuda, Eric K., Costa, Luciano da F.
Several natural and theoretical networks can be broken down into smaller portions, or subgraphs corresponding to neighborhoods. The more frequent of these neighborhoods can then be understood as motifs of the network, being therefore important for be
Externí odkaz: http://arxiv.org/abs/2204.09104
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje