Evaluation of Rules for Coping with Insufficient Data in Constraint-Based Search Algorithms

2014 ◽  
pp. 190-205
Author(s):  
Martijn de Jongh ◽  
Marek J. Druzdzel
Keyword(s):  
Search Algorithms ◽  
Insufficient Data

The Local Search Algorithms for Maximum 3-Satisfiablility Problem

2010 ◽  
Vol 33 (7) ◽  
pp. 1127-1139
Author(s):  
Da-Ming ZHU ◽  
Shao-Han MA ◽  
Ping-Ping ZHANG
Keyword(s):  
Local Search ◽  
Search Algorithms ◽  
Local Search Algorithms

PARALLEL DATA SEARCH ALGORITHMS AND THEIR IMPLEMENTATION ON THE CUDA PLATFORM

2018 ◽  
Vol 65 ◽  
pp. 55-62
Author(s):  
S. V. Skvortsov ◽  
◽  
T. A. Fetisova ◽  
D. V. Fetisov ◽  
◽  
...  
Keyword(s):  
Search Algorithms ◽  
Parallel Data ◽  
Data Search

scholarly journals FREEDOM OF THOUGHT

2020 ◽  
Vol 37 (2) ◽  
pp. 1-8
Author(s):  
David Schmidtz
Keyword(s):  
Search Algorithms ◽  
Internet Search ◽  
Emerging Issues ◽  
Freedom Of Thought

Abstract This essay introduces basic issues that make up the topic of freedom of thought, including newly emerging issues raised by the current proliferation of Internet search algorithms.

scholarly journals Quantum-walk-based search algorithms with multiple marked vertices

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
G. A. Bezerra ◽  
P. H. G. Lugão ◽  
R. Portugal
Keyword(s):  
Quantum Walk ◽  
Search Algorithms

scholarly journals Comment on “Individual heterozygosity predicts translocation success in threatened desert tortoises”

Science ◽  
2021 ◽  
Vol 372 (6546) ◽  
pp. eabg2673
Author(s):  
Philip W. Hedrick
Keyword(s):  
High Mortality ◽  
Unknown Origin ◽  
Insufficient Data ◽  
Desert Tortoise ◽  
Allelic Dropout

Scott et al. (Reports, 27 November 2020, p. 1086) suggest, on the basis of conclusions obtained from a desert tortoise reintroduction program, that higher genomic heterozygosity should be used to identify individuals for successful translocation. I contend that this recommendation is questionable given these relocated tortoises’ unknown origin, their high mortality, insufficient data on resident tortoises and other components of fitness, and potential allelic dropout.

scholarly journals Implementation of efficient quantum search algorithms on NISQ computers

2021 ◽  
Vol 20 (7) ◽  
Author(s):  
Kun Zhang ◽  
Pooja Rao ◽  
Kwangmin Yu ◽  
Hyunkyung Lim ◽  
Vladimir Korepin
Keyword(s):  
Search Algorithms ◽  
Quantum Search ◽  
Quantum Search Algorithms

scholarly journals 658 An Audit of Frequency of Cancer Genetics Referral in Patients with a Family History of Colorectal Cancer

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
M Abbakar ◽  
T James ◽  
P Boxall ◽  
M Lim
Keyword(s):  
Family History ◽  
High Risk ◽  
Hereditary Cancer ◽  
Risk Category ◽  
Average Risk ◽  
Insufficient Data ◽  
High Risk Patients ◽  
Amsterdam Criteria ◽  
Family History Questionnaire ◽  
Risk Patients

Abstract Introduction Guidelines on the management of hereditary colorectal cancers were updated in 2019. In this study, data from patients within the colonoscopy surveillance programme for hereditary cancer at York Teaching Hospitals Trust were analysed to assess category of risk and appropriateness of referrals to regional geneticists. Method After examination of electronic records and clinical notes, patients were assigned a risk category of average, moderate or high according to the Amsterdam criteria and latest BSG/ACPGBI/UKCGG guidelines. Patients were then assessed to see if a concurrent referral had been made to the regional cancer genetic services. Results There were 228 patients. 72(31.6%) patients were in the average, 81(35.5%) in the moderate and 41(18%) were in the high-risk category. 34 (14.9%) patients with insufficient data and/or assessments were in the indeterminate category. 18 of 72 (25%) patients with average risk were unnecessarily referred to the regional genetics team, while 5/41(12%) of high-risk patients were not. A large proportion of patients with insufficient data (19/34, 55.8%) were rightly or wrongly, referred to the regional genetics team. Conclusions Assessment of hereditary cancer risk is difficult in the absence of good quality information. Risk assessment may be improved with use of a dedicated family history questionnaire/template - this facilitates identification of high-risk patients that benefit most from referral to geneticists.

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