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1Revolutionizing Medical Coding in Clinical Trials with AI
D. Gayathri. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 8 (2): 191-196 (April 2024)
4 months ago by @ijtsrd
show all tags
privacy,
medical
processing,
coding,
Artificialintelligence
natural
language
data
regulatory
scalability,
clinical
intelligence,
accuracy,
learning,
compliance
efficiency,
machine
cost-effectiveness,
trials,
privacy,medicalprocessing,coding,Artificialintelligencenaturallanguagedataregulatoryscalability,clinicalintelligence,accuracy,learning,complianceefficiency,machinecost-effectiveness,trials,
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1HEART DISEASE DIAGNOSIS WITH TREE STRUCTURAL NAÏVE BAYES
H. marid Alzamili | Ali Hasan Ali. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4 (5): 134-143 (May 2023)
a year ago by @centralasian_20
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disease,
Heart
learning,
mining
data
machine
naïve
bayes,
disease,Heartlearning,miningdatamachinenaïvebayes,
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1Natural Language Processing Based Disaster Management Framework
G. |. CENTRAL ASIAN JOURNAL OF MEDICAL AND NATURAL SCIENCE, 4 (1): 72-96 (January 2023)
a year ago by @centralasian_20
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ProcessingData
Learning,
Analysis,
Data
Language
Natural
Big
Machine
Sentiment
ProcessingDataLearning,Analysis,DataLanguageNaturalBigMachineSentiment
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1The 2023 release of Cloudy
M. Chatzikos, S. Bianchi, F. Camilloni, P. Chakraborty, C. Gunasekera, F. Guzmán, J. Milby, A. Sarkar, G. Shaw, P. van Hoof and 1 other author(s). (2023)cite arxiv:2308.06396Comment: 18 pages, 10 figures, accepted for publication in RMxAA.
a year ago by @fboulang
show all tags
data
data
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1The current and future uses of machine learning in ecosystem service research
M. Scowen, I. Athanasiadis, J. Bullock, F. Eigenbrod, and S. Willcock. Science of The Total Environment, (December 2021)
a year ago by @jascal_panetzky
show all tags
Validation
ecostudy
Methodology
data
services
Ecosystem
learning
Data-driven
modelling
Big
ecomodelling
Machine
ValidationecostudyMethodologydataservicesEcosystemlearningData-drivenmodellingBigecomodellingMachine
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1Data-driven longitudinal characterization of neonatal health and morbidity
D. Francesco, J. Reiss, J. Roger, A. Tang, A. Chang, M. Becker, T. Phongpreecha, C. Espinosa, S. Morin, E. Berson and 23 other author(s). Science Translational Medicine, 15 (683): eadc9854 (2023)
2 years ago by @becker
show all tags
myown
project:2023-tracking
data
health
neonatal
paper:fastcor
longitudinal
myownproject:2023-trackingdatahealthneonatalpaper:fastcorlongitudinal
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2Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions
{. Schouten, {. Bueno, W. Duivesteijn, and M. Pechenizkiy. Data Mining and Knowledge Discovery, 36 (1): 379--413 (January 2022)Funding Information: This research is supported by EDIC project funded by NWO. We thank the EDIC consortium and the ZGT hospital for allowing us to analyse the data from the DIALECT-2 study. We especially thank Niala Den Braber (PhD candidate at Universiteit Twente and researcher internal medicine at ZGT hospital) and prof. dr. Goos Laverman (internist-nephrologist at ZGT hospital) for giving us clinical valuation of our findings. In addition, we thank our colleagues dr. Robert Peharz for giving us useful insights on Markov chains and DBNs and dr. Maryam Tavakol for guiding us towards the MovieLens dataset..
2 years ago by @tobias.koopmann
show all tags
Markov
medical
scoring
Sequential
functions
chains
data
Information-theoretic
Model
Mining
Exceptional
MarkovmedicalscoringSequentialfunctionschainsdataInformation-theoreticModelMiningExceptional
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1Analysis of Decoding Plaintext Data Using Enhanced Hamming Code Techniques
A. M.. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 6 (1): 912-914 (December 2021)
2 years ago by @ijtsrd
show all tags
code
Letter
and
Plaintext
Data
Decode
ASCII
Parity
Decoded
key
codeLetterandPlaintextDataDecodeASCIIParityDecodedkey
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1A Meliorated Kashida Based Approach for Arabic Text Steganography
A. Alhusban, and J. Alnihoud. (2017)
2 years ago by @shamerjose
show all tags
data
network
information
datanetworkinformation
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1Greedy Cluster Based Routing for Wireless Sensor Networks
M. Parthasarathi, and D. Vajravel. (2017)
2 years ago by @shamerjose
show all tags
data
network
information
datanetworkinformation
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1Multifractal detrended moving average analysis of Kepler stars with surface differential rotation traces
D. de Freitas, M. Nepomuceno, J. Cordeiro, M. Chagas, and J. Medeiros. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 488 (3): 3274-3297 (2019)
2 years ago by @ppgfis_ufc_br
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rotation;
{methods:
stars:
solar-type}
data
analysis;
rotation;{methods:stars:solar-type}dataanalysis;
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1New Suns in the Cosmos. V. Stellar Rotation and Multifractality in Active Kepler Stars
D. de Freitas, M. Nepomuceno, L. Rios, M. Chagas, and J. Medeiros. ASTROPHYSICAL JOURNAL, (2019)
2 years ago by @ppgfis_ufc_br
show all tags
solar-type;
{methods:
stars:
rotation}
data
analysis;
activity;
Sun:
solar-type;{methods:stars:rotation}dataanalysis;activity;Sun:
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1Sherlock N-overlap: Invasive Normalization and Overlap Coefficient for the Similarity Analysis Between Source Code
F. Allyson, M. Danilo, S. Jose, and B. Giovanni. IEEE TRANSACTIONS ON COMPUTERS, 68 (5): 740-751 (2019)
2 years ago by @ppgfis_ufc_br
show all tags
code
conformity}
tool;
detection;
method
normalization;
{Source
of
data
preprocessing;
similarity
investigation
codeconformity}tool;detection;methodnormalization;{Sourceofdatapreprocessing;similarityinvestigation
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1Stellar cycles from photometric data: CoRoT stars
C. Lopes, I. Leao, D. de Freitas, B. Martins, M. Catelan, and J. Medeiros. ASTRONOMY & ASTROPHYSICS, (2015)
2 years ago by @ppgfis_ufc_br
show all tags
{dynamo;
evolution}
methods:
stars:
data
analysis;
activity;
Sun:
fields;
magnetic
{dynamo;evolution}methods:stars:dataanalysis;activity;Sun:fields;magnetic
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1New Suns in the Cosmos. IV. The Multifractal Nature of Stellar Magnetic Activity in Kepler Cool Stars
D. de Freitas, M. Nepomuceno, M. de Souza, I. Leao, M. Chagas, A. Costa, B. Martins, and J. Medeiros. ASTROPHYSICAL JOURNAL, (2017)
2 years ago by @ppgfis_ufc_br
show all tags
solar-type;
{methods:
stars:
rotation}
data
analysis;
activity;
Sun:
solar-type;{methods:stars:rotation}dataanalysis;activity;Sun:
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1NEW SUNS IN THE COSMOS. III. MULTIFRACTAL SIGNATURE ANALYSIS
D. de Freitas, M. Nepomuceno, P. de Moraes Junior, C. Lopes, M. Chagas, J. Bravo, A. Costa, B. Martins, J. Medeiros, and I. Leao. ASTROPHYSICAL JOURNAL, (2016)
2 years ago by @ppgfis_ufc_br
show all tags
rotation;
solar-type;
{methods:
stars:
rotation}
data
analysis;
Sun:
rotation;solar-type;{methods:stars:rotation}dataanalysis;Sun:
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1NEW SUNS IN THE COSMOS?
D. de Freitas, I. Leao, C. Lopes, F. Paz-Chinchon, B. Martins, S. Alves, J. Medeiros, and M. Catelan. ASTROPHYSICAL JOURNAL LETTERS, (2013)
2 years ago by @ppgfis_ufc_br
show all tags
rotation;
solar-type;
{methods:
stars:
rotation}
data
analysis;
variables:
Sun:
general;
rotation;solar-type;{methods:stars:rotation}dataanalysis;variables:Sun:general;
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2Fast Point Cloud Registration using Semantic Segmentation
G. Truong, S. Gilani, S. Islam, and D. Suter. 2019 Digital Image Computing: Techniques and Applications (DICTA), page 1-8. (December 2019)DST Best Science Paper Award.
3 years ago by @dsuter
show all tags
registration;deep
algorithm;visual
(artificial
data
learning;semantic
registration;image
graphics;image
scale
learning;point
sets;optimal
intelligence);point
point
cloud
registration;point-cloud
computer
information;deep
segmentation;large
data;semantic
matches;semantic
data-sets;point
segmentation;learning
data;large
segmentation
registration
registration;deepalgorithm;visual(artificialdatalearning;semanticregistration;imagegraphics;imagescalelearning;pointsets;optimalintelligence);pointpointcloudregistration;point-cloudcomputerinformation;deepsegmentation;largedata;semanticmatches;semanticdata-sets;pointsegmentation;learningdata;largesegmentationregistration
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1A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006
M. Haylock, N. Hofstra, A. Klein Tank, E. Klok, P. Jones, and M. New. Journal of Geophysical Research Atmospheres, 113 (20): D20119 (2008)
3 years ago by @msteininger
show all tags
data
E-OBS,Europe,data,observation
dataE-OBS,Europe,data,observation
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3Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality
C. Sandrock, M. Herde, A. Calma, D. Kottke, and B. Sick. International Joint Conference on Neural Networks (IJCNN), page 1--8. IEEE, (2019)
3 years ago by @ies
show all tags
confidences;{\gamma}-
confidence
(artificial
evaluation;probabilistic
likelihood
estimation;pattern
outputs;intelligent
mining;learning
quality;class
vote;label
models;{\beta}-confidence
classification;probability;multiple
annotators;multiple
assignment;self-reported
machines
posses
model;nonnormalized
levels;{\alpha}-confidence;benevolent
confidences;numerical
data
annotators;expertise
uncertain
intelligence);maximum
evaluation;graphical
majority
weighted
different
annotators;confidence
confidences;{\gamma}-confidence(artificialevaluation;probabilisticlikelihoodestimation;patternoutputs;intelligentmining;learningquality;classvote;labelmodels;{\beta}-confidenceclassification;probability;multipleannotators;multipleassignment;self-reportedmachinespossesmodel;nonnormalizedlevels;{\alpha}-confidence;benevolentconfidences;numericaldataannotators;expertiseuncertainintelligence);maximumevaluation;graphicalmajorityweighteddifferentannotators;confidence
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publications (hide)706
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