A data-driven Bayesian optimisation framework for the design and stacking sequence selection of increased notched strength laminates

2021 ◽  
pp. 109347
Author(s):  
T.R.C. Chuaqui ◽  
A.T. Rhead ◽  
R. Butler ◽  
C. Scarth
Keyword(s):  
Data Driven ◽  
Stacking Sequence ◽  
Sequence Selection ◽  
Notched Strength ◽  
Selection Of

scholarly journals Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers

2021 ◽  
Author(s):  
Laure Fournier ◽  
Lena Costaridou ◽  
Luc Bidaut ◽  
Nicolas Michoux ◽  
Frederic E. Lecouvet ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Quantitative Imaging ◽  
A Priori ◽  
External Validation ◽  
Data Driven ◽  
Imaging Biomarkers ◽  
Clinical Validation ◽  
Biological Processes ◽  
Imaging Data ◽  
Selection Of

Abstract Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

scholarly journals KELONGGARAN PEMILIHAN DAN PENEMPATAN LEKSIKON SEBAGAI FITUR KESANTUNAN BERTUTUR MASYARAKAT JAWA PESISIR

HUMANIKA ◽  
2015 ◽  
Vol 22 (2) ◽  
pp. 34
Author(s):  
M M. Suryadi
Keyword(s):  
Cultural Factors ◽  
Coastal Communities ◽  
Coastal Community ◽  
Java Language ◽  
Sequence Selection ◽  
Language Alternation ◽  
Selection Of

Politeness of Java coastal communities have a uniqueness when compared with the politeness of standard Javalanguage. Distinctiveness of its identity can beusedas a coastal community. Characteristic politeness Javanese coastal communities visible in the selection and placement of the lexiconon syntagmatic sequence. Selection of the lexicon is determined more by socio-cultural factors Javanese coastal communities. Placement of the lexicon is determined assuming more speakers than the alternation rules that apply in the standard Java language. The selection and placement of the lexicon in politeness Java coastal communities freed the standard Java language alternation rules.

Data driven selection of DRX for energy efficient 5G RAN

2017 ◽  
Author(s):  
Diarmuid Corcoran ◽  
Loghman Andimeh ◽  
Andreas Ermedahl ◽  
Per Kreuger ◽  
Christian Schulte
Keyword(s):  
Energy Efficient ◽  
Data Driven ◽  
Selection Of

scholarly journals Precision Medicine

2019 ◽  
Vol 6 (1) ◽  
pp. 263-286 ◽  
Author(s):  
Michael R. Kosorok ◽  
Eric B. Laber
Keyword(s):  
Health Care ◽  
Precision Medicine ◽  
Decision Rules ◽  
Data Driven ◽  
Care Process ◽  
Treatment Regimes ◽  
Specific Diet ◽  
Recommended Action ◽  
Selection Of

Precision medicine seeks to maximize the quality of health care by individualizing the health-care process to the uniquely evolving health status of each patient. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in support of evidence-based, i.e., data-driven, decision making. Precision medicine is formalized as a treatment regime that comprises a sequence of decision rules, one per decision point, which map up-to-date patient information to a recommended action. The potential actions could be the selection of which drug to use, the selection of dose, the timing of administration, the recommendation of a specific diet or exercise, or other aspects of treatment or care. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimes that maximize some cumulative clinical outcome. In this review, we provide an overview of this vibrant area of research and present important and emerging challenges.

DATABASE SUPPORT FOR DATA-DRIVEN SCIENTIFIC APPLICATIONS IN THE GRID

2003 ◽  
Vol 13 (02) ◽  
pp. 245-271 ◽  
Author(s):  
SIVARAMAKRISHNAN NARAYANAN ◽  
TAHSIN KURC ◽  
UMIT CATALYUREK ◽  
JOEL SALTZ
Keyword(s):  
Distributed Databases ◽  
Experimental Results ◽  
Data Driven ◽  
Software System ◽  
Scientific Datasets ◽  
Database Support ◽  
Main Components ◽  
Efficient Selection ◽  
Selection Of ◽  
Efficient Transfer

In this paper we describe a services oriented software system to provide basic database support for efficient execution of applications that make use of scientific datasets in the Grid. This system supports two core operations: efficient selection of the data of interest from distributed databases and efficient transfer of data from storage nodes to compute nodes for processing. We present its overall architecture and main components and describe preliminary experimental results.

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