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publications (hide)65
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1A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data
N. Ahmadi, {. Nguyen, M. Sedlmayr, and M. Wolfien. Scientific reports, (Jan 27, 2024)
9 months ago by @scadsfct
show all tags
FIS_scads
Factual,
Learning,
Health
learning
Electronic
Informatics,
Databases,
Humans,
machine
topic_lifescience
Medical
Records
yaff
FIS_scadsFactual,Learning,HealthlearningElectronicInformatics,Databases,Humans,machinetopic_lifescienceMedicalRecordsyaff
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2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement
T. Vargis, and S. Ghiasvand. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, (January 2022)arXiv:2402.05114 cs.
8 months ago by @ghiasvan
show all tags
Parallel,
myOwn
Learning
and
Computer
Cluster
Distributed,
Computing,
Science
Machine
Parallel,myOwnLearningandComputerClusterDistributed,Computing,ScienceMachine
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1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving
D. Li, and O. Okhrin. Commun Eng, 3 (1): 147 (October 2024)
7 months ago by @scadsfct
show all tags
driving
framework
platform-agnostic
autonomous
deep
xack
learning
reinforcement
Sim2Real
drivingframeworkplatform-agnosticautonomousdeepxacklearningreinforcementSim2Real
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1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
D. Nam, J. Chapiro, V. Paradis, T. Seraphin, and J. Kather. JHEP Rep., 4 (4): 100443 (April 2022)
11 months ago by @scadsfct
show all tags
a
imaging
or
disease
liver
multivariable
TACE
non-alcoholic
multimodal
artificial
prediction
support
integration
NAFLD
TRIPOD
deep
neural
Digital
network
transarterial
fatty
topic_lifescience
Diagnosis
DICOM
ML
steatohepatitis
microvascular
convolutional
NASH
in
HCC
AI
Communications
images
intelligence
hepatocellular
Reporting
chemoembolisation
system
Medicine
carcinoma
invasion
Transparent
Individual
slide
machine
zno
MVI
Prognosis
CNN
data
for
learning
whole
WSIs
of
and
Imaging
diagnostic
model
aimagingordiseaselivermultivariableTACEnon-alcoholicmultimodalartificialpredictionsupportintegrationNAFLDTRIPODdeepneuralDigitalnetworktransarterialfattytopic_lifescienceDiagnosisDICOMMLsteatohepatitismicrovascularconvolutionalNASHinHCCAICommunicationsimagesintelligencehepatocellularReportingchemoembolisationsystemMedicinecarcinomainvasionTransparentIndividualslidemachineznoMVIPrognosisCNNdataforlearningwholeWSIsofandImagingdiagnosticmodel
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1Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology
Q. Zeng, C. Klein, S. Caruso, P. Maille, N. Laleh, D. Sommacale, A. Laurent, G. Amaddeo, D. Gentien, A. Rapinat and 10 other author(s). J. Hepatol., 77 (1): 116--127 (July 2022)
11 months ago by @scadsfct
show all tags
image
immune
pathology
gene
deep
signatures;
learning
whole
intelligence
artificial
slide
topic_lifescience
zno
imageimmunepathologygenedeepsignatures;learningwholeintelligenceartificialslidetopic_lifesciencezno
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1Artificial intelligence-based detection of FGFR3 mutational status directly from routine histology in bladder cancer: A possible preselection for molecular testing?
C. Loeffler, N. Ortiz Bruechle, M. Jung, L. Seillier, M. Rose, N. Laleh, R. Knuechel, T. Brinker, C. Trautwein, N. Gaisa and 1 other author(s). Eur. Urol. Focus, 8 (2): 472--479 (March 2022)
11 months ago by @scadsfct
show all tags
deep
cancer
therapy
for
learning
intelligence
Bladder
mutations
artificial
Molecular
fibroblast
receptor
testing
topic_lifescience
growth
zno
factor
FGFR3
deepcancertherapyforlearningintelligenceBladdermutationsartificialMolecularfibroblastreceptortestingtopic_lifesciencegrowthznofactorFGFR3
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2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, and E. Rahm. arXiv preprint arXiv:2409.01329, (September 2024)
9 months ago by @scadsfct
show all tags
(cs.LG)
xack
FOS
learning
ep
(cs.CV)
(cs.CR)
sciences
Security
machine
Vision
Computer
Cryptography
information
Pattern
area_bigdata
yaff
area_responsibleai
Recognition
(cs.LG)xackFOSlearningep(cs.CV)(cs.CR)sciencesSecuritymachineVisionComputerCryptographyinformationPatternarea_bigdatayaffarea_responsibleaiRecognition
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1Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning
P. Kerschke, and H. Trautmann. Evol. Comput., 27 (1): 99--127 (2019)
11 months ago by @scadsfct
show all tags
single-objective
learning
black-box
analysis
automated
exploratory
selection
optimization
continuous
machine
zno
algorithm
landscape
single-objectivelearningblack-boxanalysisautomatedexploratoryselectionoptimizationcontinuousmachineznoalgorithmlandscape
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1Automated algorithm selection: Survey and perspectives
P. Kerschke, H. Hoos, F. Neumann, and H. Trautmann. Evol. Comput., 27 (1): 3--45 (2019)
11 months ago by @scadsfct
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feature-based
metalearning
configuration
streams
data
approaches
learning
analysis
automated
exploratory
selection
optimisation
combinatorial
continuous
machine
zno
algorithm
landscape
feature-basedmetalearningconfigurationstreamsdataapproacheslearninganalysisautomatedexploratoryselectionoptimisationcombinatorialcontinuousmachineznoalgorithmlandscape
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1Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning
L. Maiello, L. Ball, M. Micali, F. Iannuzzi, N. Scherf, R. Hoffmann, M. Gama de Abreu, P. Pelosi, and R. Huhle. Front. Physiol., (2021)
11 months ago by @scadsfct
show all tags
ARDS
uNet
transfer
recruitment
lung
deep
learning
index
segmentation
zno
COVID-19
Jaccard
ARDSuNettransferrecruitmentlungdeeplearningindexsegmentationznoCOVID-19Jaccard
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1Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology
N. Ghaffari Laleh, H. Muti, C. Loeffler, A. Echle, O. Saldanha, F. Mahmood, M. Lu, C. Trautwein, R. Langer, B. Dislich and 13 other author(s). Med. Image Anal., 79 (102474): 102474 (July 2022)
11 months ago by @scadsfct
show all tags
Convolutional
pathology
Multiple-Instance
deep
neural
learning
networks
Weakly-supervised
intelligence
Learning;
artificial
transformers;
topic_lifescience
Vision
zno
Computational
ConvolutionalpathologyMultiple-InstancedeepneurallearningnetworksWeakly-supervisedintelligenceLearning;artificialtransformers;topic_lifescienceVisionznoComputational
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1BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
A. Avila Santos, B. de Almeida, R. Bonidia, P. Stadler, P. Stefanic, I. Mandic-Mulec, U. Rocha, D. Sanches, and A. de Carvalho. RNA Biology, 21 (1): 410–421 (March 2024)
8 months ago by @scadsfct
show all tags
deep
RNA
non-coding
feature
learning
zno
extraction
BioDeepfuse
classification
deepRNAnon-codingfeaturelearningznoextractionBioDeepfuseclassification
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1Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.
M. Bauer, and C. Augenstein. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, volume 35 of FedCSIS 2023, page 93–101. IEEE, (September 2023)
8 months ago by @scadsfct
show all tags
Study
data
Vision
Computer
learning
Self-Supervised
Unlabelled
yaff
Comparative
StudydataVisionComputerlearningSelf-SupervisedUnlabelledyaffComparative
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2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning
M. Novitasari, J. Quaas, and M. Rodrigues. Environmental Data Science, (2024)
8 months ago by @scadsfct
show all tags
rates
forecasting
machine
autoconversion
learning
satellite
yaff
ratesforecastingmachineautoconversionlearningsatelliteyaff
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1Common features in lncRNA annotation and classification: A survey
C. Klapproth, R. Sen, P. Stadler, S. Findeiß, and J. Fallmann. Noncoding RNA, 7 (4): 77 (December 2021)
11 months ago by @scadsfct
show all tags
sequence
coding
lncRNA
feature
machine
problems
learning
extraction
yaff
classification
sequencecodinglncRNAfeaturemachineproblemslearningextractionyaffclassification
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1Continual learning autoencoder training for a particle-in-cell simulation via streaming
P. Stiller, V. Makdani, F. Pöschel, R. Pausch, A. Debus, M. Bussmann, and N. Hoffmann. (2022)
7 months ago by @scadsfct
show all tags
imported
autoencoder
particle-in-cell
simulation
learning
training
zno
Continual
importedautoencoderparticle-in-cellsimulationlearningtrainingznoContinual
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1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective
R. Knauer, and E. Rodner. KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI, Berlin, Germany, September 26--29, 2023, Proceedings, page 114--129. Berlin, Heidelberg, Springer-Verlag, (2023)
7 months ago by @scadsfct
show all tags
mixed-integer
selection
optimization
meta-learning
machine
learning
zno
conic
interpretable
cost-sensitive
best
subset
mixed-integerselectionoptimizationmeta-learningmachinelearningznoconicinterpretablecost-sensitivebestsubset
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1Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer
S. Brockmoeller, A. Echle, N. Ghaffari Laleh, S. Eiholm, M. Malmstrøm, T. Plato Kuhlmann, K. Levic, H. Grabsch, N. West, O. Saldanha and 7 other author(s). J. Pathol., 256 (3): 269--281 (March 2022)
11 months ago by @scadsfct
show all tags
metastasis;
bowel
predictive
adipose
intelligence
digital
biomarker
artificial
prediction
zno
tissue;
pathology
inflamed
deep
cancer
learning
LNM
pT2
pT1
AI;
colorectal
and
topic_lifescience
new
early
metastasis;bowelpredictiveadiposeintelligencedigitalbiomarkerartificialpredictionznotissue;pathologyinflameddeepcancerlearningLNMpT2pT1AI;colorectalandtopic_lifesciencenewearly
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1Deep learning improves pancreatic cancer diagnosis using RNA-based variants
A. Al-Fatlawi, N. Malekian, S. Garc\'ıa, A. Henschel, I. Kim, A. Dahl, B. Jahnke, P. Bailey, S. Bolz, A. Poetsch and 4 other author(s). Cancers (Basel), 13 (11): 2654 (May 2021)
11 months ago by @scadsfct
show all tags
study
transcriptome-wide
deep
cancer
topic_lifescience
association
learning
pancreatic
pancreatitis
zno
chronic
studytranscriptome-widedeepcancertopic_lifescienceassociationlearningpancreaticpancreatitisznochronic
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1Deep reinforcement learning with artificial microswimmers
R. Pradip, and F. Cichos. Emerging Topics in Artificial Intelligence (ETAI) 2022, 12204, page 104--110. SPIE, (2022)
9 months ago by @scadsfct
show all tags
microswimmers
artificial
nopdf
deep
learning
topic_physchemistry
reinforcement
microswimmersartificialnopdfdeeplearningtopic_physchemistryreinforcement
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publications (hide)65
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1A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data

2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement

1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving

1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction

1Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology

1Artificial intelligence-based detection of FGFR3 mutational status directly from routine histology in bladder cancer: A possible preselection for molecular testing?

2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning

1Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning

1Automated algorithm selection: Survey and perspectives

1Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning

1Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology

1BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

1Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.

2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning

1Common features in lncRNA annotation and classification: A survey

1Continual learning autoencoder training for a particle-in-cell simulation via streaming

1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective

1Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer

1Deep learning improves pancreatic cancer diagnosis using RNA-based variants

1Deep reinforcement learning with artificial microswimmers

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