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2HIGH PERFORMANCE COMPUTING ON THE RASPBERRY PI
E. Hodgess. International Journal of Computational Science and Information Technology (IJCSITY), (February 2022)
17 days ago by @ijcsity
show all tags
machine
simulation
learning
machinesimulationlearning
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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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2Multi-agent system application for music features extraction, meta-classification and context analysis
J. Perez-Marcos, D. Jimenez-Bravo, J. De Paz, G. Villarrubia Gonzalez, V. Lopez, and A. Gil. Knowledge and Information Systems, 62 (1): 401--422 (Jan 1, 2020)
8 months ago by @sop2-ffzg
show all tags
Social
Auto-classification
Performance
Multi-label
analysis
intelligence
classification
Meta-classifiers
Single-label
Emotional
Distributed
Music
processing
Genre
information
Artificial
Twitter
recommendation
learning
networks
from:kamber
Machine
Multi-agent
systems
Contextual
evaluation
Last.fm
Multi-classification
SocialAuto-classificationPerformanceMulti-labelanalysisintelligenceclassificationMeta-classifiersSingle-labelEmotionalDistributedMusicprocessingGenreinformationArtificialTwitterrecommendationlearningnetworksfrom:kamberMachineMulti-agentsystemsContextualevaluationLast.fmMulti-classification
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2Multi-agent system application for music features extraction, meta-classification and context analysis
J. Perez-Marcos, D. Jimenez-Bravo, J. De Paz, G. Villarrubia Gonzalez, V. Lopez, and A. Gil. Knowledge and Information Systems, 62 (1): 401--422 (Jan 1, 2020)
8 months ago by @kamber
show all tags
Social
Auto-classification
Performance
Multi-label
analysis
intelligence
classification
Meta-classifiers
Single-label
Emotional
Distributed
Music
processing
Genre
information
Artificial
Twitter
recommendation
learning
networks
Machine
Multi-agent
systems
Contextual
evaluation
Last.fm
Multi-classification
SocialAuto-classificationPerformanceMulti-labelanalysisintelligenceclassificationMeta-classifiersSingle-labelEmotionalDistributedMusicprocessingGenreinformationArtificialTwitterrecommendationlearningnetworksMachineMulti-agentsystemsContextualevaluationLast.fmMulti-classification
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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
show all tags
disease,
Heart
learning,
mining
data
machine
naïve
bayes,
disease,Heartlearning,miningdatamachinenaïvebayes,
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1Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature
E. Berson, A. Sreenivas, T. Phongpreecha, A. Perna, F. Grandi, L. Xue, N. Ravindra, N. Payrovnaziri, S. Mataraso, Y. Kim and 9 other author(s). Nature Communications, 14 (1): 4947 (2023)
a year ago by @becker
show all tags
deconvolution
genome
alzheimer
myown
epigenetics
machine
learning
deconvolutiongenomealzheimermyownepigeneticsmachinelearning
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1The Use of Machine Learning and Neural Networks in the Digital Economy and International Digital Integration
D. Okhunov. Journal of Ethics and Diversity in International Communication, 3 (2): 79-84 (February 2023)
a year ago by @openaccess_20
show all tags
artificial
algorithms,
intelligence,
learning,
neural
neurocybernetic
machine
networks
approach,
logical
artificialalgorithms,intelligence,learning,neuralneurocyberneticmachinenetworksapproach,logical
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1Predicting Pre-Owned Car Prices Using Machine Learning
M. Priya. CENTRAL ASIAN JOURNAL OF MEDICAL AND NATURAL SCIENCE, 4 (4): 187-203 (June 2023)
a year ago by @centralasian_20
show all tags
Predicting
Prices,
Car
Pre-Owned
Random
Forest
Regression,
Tree,
Decision
,
LearningLinear
Machine
PredictingPrices,CarPre-OwnedRandomForestRegression,Tree,Decision,LearningLinearMachine
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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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3Can deep learning beat numerical weather prediction?
M. Schultz, C. Betancourt, B. Gong, F. Kleinert, M. Langguth, L. Leufen, A. Mozaffari, and S. Stadtler. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379 (2194): 20200097 (February 2021)Publisher: Royal Society.
a year ago by @jascal_panetzky
show all tags
recognition,
learning,
deep
prediction,
machine
AI
pattern
spatiotemporal
numerical
weather
ecomodelling
recognition,learning,deepprediction,machineAIpatternspatiotemporalnumericalweatherecomodelling
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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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1A guide to machine learning for biologists
J. Greener, S. Kandathil, L. Moffat, and D. Jones. Nature Reviews Molecular Cell Biology, 23 (1): 40--55 (2022)
2 years ago by @becker
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nature
machine
learning
guide
citedby:scholar:timestamp:2022-6-29
biologists
citedby:scholar:count:72
naturemachinelearningguidecitedby:scholar:timestamp:2022-6-29biologistscitedby:scholar:count:72
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1Leukocyte telomere dynamics across gestation in uncomplicated pregnancies and associations with stress
D. Panelli, S. Leonard, R. Wong, M. Becker, J. Mayo, E. Wu, A. Girsen, I. Gotlib, N. Aghaeepour, M. Druzin and 1 other author(s). BMC Pregnancy and Childbirth, 22 (1): 1--12 (2022)
3 years ago by @becker
show all tags
telomeres
myown
stress
pregnancy
telomere
machine
learning
telomeresmyownstresspregnancytelomeremachinelearning
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1TEMPORALLY EXTENDED ACTIONS FOR REINFORCEMENT LEARNING BASED SCHEDULERS
P. Ojha, S. Thota, V. M, and M. Tahilianni. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 4 (3/4): 01 - 18 (November 2015)
3 years ago by @leninsha
show all tags
Preemption
Options
Actions
Scheduler
Operating
Machine
System
Extension
Learning
of
Temporal
Reinforcement
Online
PreemptionOptionsActionsSchedulerOperatingMachineSystemExtensionLearningofTemporalReinforcementOnline
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1Automatic Covid 19 Infected Chest X Ray Image Classification using Support Vector Machine
M. Hossen. International Journal of Trend in Scientific Research and Development, 5 (4): 626-632 (June 2021)
3 years ago by @ijtsrd
show all tags
Chest
(CM)
Support
Confusion
(IP)
Image
Processing
Machine
(ML)
Matrix
Learning
X-Ray
Covid-19
(SVM)
Vector
Chest(CM)SupportConfusion(IP)ImageProcessingMachine(ML)MatrixLearningX-RayCovid-19(SVM)Vector
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1Deleterious and Protective Psychosocial and Stress-Related Factors Predict Risk of Spontaneous Preterm Birth
M. Becker, J. Mayo, N. Phogat, C. Quaintance, A. Laborde, L. King, I. Gotlib, B. Gaudilliere, M. Angst, G. Shaw and 3 other author(s). American journal of perinatology, (May 2021)
3 years ago by @becker
show all tags
project:bmbf
myown
stress
machine
birth
preterm
learning
project:bmbfmyownstressmachinebirthpretermlearning
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1Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset
I. Stelzer, M. Ghaemi, X. Han, K. Ando, J. Hedou, D. Feyaerts, L. Peterson, K. Rumer, E. Tsai, E. Ganio and 28 other author(s). Science Translational Medicine, (2021)
3 years ago by @becker
show all tags
labor
project:bmbf
myown
mining
of
pregnancy
data
paper:cordis
machine
multiomics
learning
onset
laborproject:bmbfmyownminingofpregnancydatapaper:cordismachinemultiomicslearningonset
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2Machine learning
T. Mitchell. McGraw-Hill, New York, NY, (2010)
4 years ago by @jaeschke
show all tags
mining
data
machine
learning
kdd
ddm
mk5.4
ml
miningdatamachinelearningkddddmmk5.4ml
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1Machine Learning in Early Genetic Detection of Multiple Sclerosis Disease: A Survey
N. Ali, M. Shaheen, M. Mabrouk, and M. AboRezka. International Journal of Computer Science & Information Technology (IJCSIT), 12 (5): 01 - 18 (October 2020)
4 years ago by @shamerjose
show all tags
Sequencing.
detection
disease
Nucleotide
learning
Microarray
Machine
sclerosis
Next
Single
Multiple
Generation
Polymorphism
early
Sequencing.detectiondiseaseNucleotidelearningMicroarrayMachinesclerosisNextSingleMultipleGenerationPolymorphismearly
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4GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Q. Nguyen, K. Lim, D. Divakaran, K. Low, and M. Chan. Proc. IEEE Conf. Communications and Network Security (CNS), page 91--99. (June 2019)
4 years ago by @annakrause
show all tags
models,
deep-learning
detection
Gradient-based
zero-day
explainable
methods,
learning,
Fingerprinting
machine
unsupervised
gradient
autoencoder,
techniques,
UGR
Records,
variational
Internet,
anomaly
statistical
dataset,
Detection,
GEE,
NetFlow
learning
network
recording,
technique,
detection,
analysis,
attack
VAE,
anomalous
Anomaly
fingerprinting
solutions,
traffic
gradient-based
models,deep-learningdetectionGradient-basedzero-dayexplainablemethods,learning,Fingerprintingmachineunsupervisedgradientautoencoder,techniques,UGRRecords,variationalInternet,anomalystatisticaldataset,Detection,GEE,NetFlowlearningnetworkrecording,technique,detection,analysis,attackVAE,anomalousAnomalyfingerprintingsolutions,trafficgradient-based
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publications (hide)76
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