Tag: Evaluating

AI/ML

Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.

Newsemia
Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation. Eur J Radiol. 2020 Jul 12;130:109153 Authors: Zopfs D, Bousabarah...
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The psychasthenia of deep space. Evaluating the "reassertion of space in critical social theory".

Newsemia
Michell, Theodore William Henry; (2002) The psychasthenia of deep space. Evaluating the “reassertion of space in critical social theory”. Doctoral thesis (Ph.D), UCL (University College...
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Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data

Newsemia
Chung, MWH; Tissot, H; (2020) Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data. Presented at: UNSPECIFIED. (In...
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Evaluating the Capability of OpenStreetMap for Estimating Vehicle Localization Error

Newsemia
Wong, K; Javanmardi, E; Javanmardi, M; Gu, Y; Kamijo, S; (2019) Evaluating the Capability of OpenStreetMap for Estimating Vehicle Localization Error. In: Proceedings of the...
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Kala Pharmaceuticals Announces Statistically Significant Results for Primary and Key Secondary Endpoints in STRIDE 3 Clinical Trial Evaluating EYSUVIS™ for Signs and Symptoms of Dry Eye Disease

Newsemia
WATERTOWN, Mass.–(BUSINESS WIRE)–Kala Pharmaceuticals, Inc. (Kala) (NASDAQ:KALA), a biopharmaceutical company focused on the discovery, development and commercialization of innovative therapies for diseases of the eye,...
AI/ML

Evaluating the severity of depressive symptoms using upper body motion captured by RGB-depth sensors and machine learning in a clinical interview setting: A preliminary study.

Newsemia
Related Articles Evaluating the severity of depressive symptoms using upper body motion captured by RGB-depth sensors and machine learning in a clinical interview setting: A...

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