Results 291 to 300 of about 1,818,152 (349)

An interpretable model for predicting the performances of asphalt mixtures comprising the chemistry composition of steel slag

Bin Lei, Jiawu Chen, Yang Yu, Lingjuan Huang, Linjie Yu, Wei Jiang   +5 more
openalex   +1 more source

Machine learning to predict metabolic-associated fatty liver disease. [PDF]

World J Gastroenterol
Cicerone O, Maestri M.
europepmc   +1 more source

Interpreting neonatal nursing care from the parents' experiences viewpoint Interpretación del cuidado de enfermería neonatal desde las experiencias y vivencias de los padres; Interpretação do cuidado da enfermagem neonatal partindo das experiências e vivências dos pais

, 2008
RUIZ DE CÁRDENAS CARMEN HELENA, G. Clemente   +1 more
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Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation. [PDF]

Front Neurol
Tang X, Tang M, Liu W, Cui S.
europepmc   +1 more source

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Interpreting Interpretation

Journal of the American Psychoanalytic Association, 2023
Interpretation of the latent meaning of manifest content is the core of the traditional approach to psychoanalytic treatment. The main purpose of such interpretation is to enhance the patient’s self-knowledge, in particular his or her awareness of unconscious wishes and their embeddedness in inner conflicts.
openaire   +2 more sources

‘Interpreters of Interpreters’

Mnemosyne, 2019
AbstractWe discuss analogies between oracular and grammatical interpretation, as reflected in our Greek and Latin sources from the Classical era to the High Empire. The two hermeneutical professions of µάντις and γραµµατικός both aim at elucidating the thought (διάνοια) involved in the interpretandum. This is a notion quite frequently made at one level
Lampinen Antti, Seppänen Minna
openaire   +2 more sources

Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning

International Conference on Human Factors in Computing Systems, 2020
Machine learning (ML) models are now routinely deployed in domains ranging from criminal justice to healthcare. With this newfound ubiquity, ML has moved beyond academia and grown into an engineering discipline.
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, R. Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan   +5 more
semanticscholar   +1 more source