Results 41 to 50 of about 7,266,292 (305)

Learning Curve of Speech Recognition [PDF]

open access: yesJournal of Digital Imaging, 2013
Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new ...
Koivikko Mika P.   +3 more
openaire   +2 more sources

Reconstructing enzyme evolution by protein engineering

open access: yesFEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler   +2 more
wiley   +1 more source

Learning curve for radical retropubic prostatectomy

open access: yesInternational Brazilian Journal of Urology, 2011
PURPOSE: The learning curve is a period in which the surgical procedure is performed with difficulty and slowness, leading to a higher risk of complications and reduced effectiveness due the surgeon's inexperience.
Fernando J. A. Saito   +5 more
doaj   +1 more source

Learning curve analysis of single-port thoracoscopic combined subsegmental resections

open access: yesFrontiers in Oncology, 2023
BackgroundCombined subsegmental surgery (CSS) is considered to be a safe and effective resection modality for early-stage lung cancer. However, there is a lack of a clear definition of the technical difficulty classification of this surgical case, as ...
Yizhou Huang   +20 more
doaj   +1 more source

Learning Curve Theory

open access: yesCoRR, 2021
Recently a number of empirical "universal" scaling law papers have been published, most notably by OpenAI. `Scaling laws' refers to power-law decreases of training or test error w.r.t. more data, larger neural networks, and/or more compute. In this work we focus on scaling w.r.t. data size $n$.
openaire   +3 more sources

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

open access: yesMolecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur   +11 more
wiley   +1 more source

The Sex Inclusive Research Framework to address sex bias in preclinical research proposals

open access: yesNature Communications
An interactive Sex Inclusive Research Framework (SIRF) supports the evaluation of in vivo and ex vivo research proposals to address the risk of sex bias in preclinical research.
Natasha A. Karp   +16 more
doaj   +1 more source

Learning curve? Which one?

open access: yesRAC: Revista de Administração Contemporânea
Learning curves have been studied for a long time. These studies provided strong support to the hypothesis that, as organizations produce more of a product, unit costs of production decrease at a decreasing rate (see Argote, 1999 for a comprehensive ...
Paulo Prochno
doaj   +1 more source

Learning Curves and p-charts for a preliminary estimation of asymptotic performances of a manufacturing process [PDF]

open access: yes, 2002
This paper presents a method for a preliminary estimation of asymptotic performances of a manufacturing process based on the knowledge of its learning curve estimated during the setting up of p-chart.
Franceschini, Fiorenzo
core   +1 more source

CEACAM1 participation in breast cancer progression

open access: yesMolecular Oncology, EarlyView.
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin   +3 more
wiley   +1 more source

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