Results 181 to 190 of about 572,458 (282)

Intent Arabic text categorisation based on different machine learning and term frequency

open access: yesIET Networks, EarlyView., 2022
Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's ...
Mohammad Fadhil Mahdi   +1 more
wiley   +1 more source

Rosette Cardiac MR Fingerprinting for Simultaneous T1, T2, T2*$$ {\mathrm{T}}_2^{\ast } $$, and Fat Fraction Mapping Using a Multi‐Echo Deep Image Prior Reconstruction

open access: yesMagnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Quantitative mapping of cardiac tissue properties is used clinically in diagnosis and monitoring of a wide variety of cardiac pathologies. Cardiac Magnetic Resonance Fingerprinting (cMRF) enables rapid and simultaneous quantification of multiple parameters in the myocardium from a single scan.
Evan Cummings   +5 more
wiley   +1 more source

Sparse dictionary learning recovers pleiotropy from human cell fitness screens. [PDF]

open access: yesCell Syst, 2022
Pan J   +9 more
europepmc   +1 more source

Opening the Black Box of Nonprofit Reputation and Volunteer Attraction With Supervised Machine Learning

open access: yesNonprofit Management and Leadership, EarlyView.
ABSTRACT With the aim to explore the potential of machine learning for nonprofit research, this article contrasts traditional linear regression with four contemporary supervised machine learning approaches. Concretely, we predict (1) reputation ratings and (2) the total number of volunteers for 4021 non‐profit organizations in the U.S.
Moritz Schmid   +2 more
wiley   +1 more source

GraphReco: Probabilistic Structure Recognition for Chemical Molecules

open access: yesChemistryOpen, EarlyView.
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang   +2 more
wiley   +1 more source

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