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publications (hide)68
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2Sleep analysis in a CLIS patient using soft-clustering: a case study
S. Adama, and M. Bogdan. Louvain-la-Neuve (Belgium), Ciaco - i6doc.com, (2023)
a month ago by @scads.ai
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Sleep
from:scadsfct
analysis
CLIS
soft-clustering
Sleepfrom:scadsfctanalysisCLISsoft-clustering
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2Application of soft-clustering to assess consciousness in a CLIS patient
S. Adama, and M. Bogdan. Brain Sci., 13 (1): 65 (December 2022)
a month ago by @scads.ai
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complexity
electrocorticogram
consciousness
spectral
from:scadsfct
analysis
extraction
features
syndrome
connectivity
completely
locked-in
soft-clustering
complexityelectrocorticogramconsciousnessspectralfrom:scadsfctanalysisextractionfeaturessyndromeconnectivitycompletelylocked-insoft-clustering
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2Assessing consciousness in patients with disorders of consciousness using soft-clustering
S. Adama, and M. Bogdan. Brain Inform., 10 (1): 16 (July 2023)
a month ago by @scads.ai
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Brain-computer
Electroencephalogram
Consciousness
consciousness
Disorders
Connectivity
from:scadsfct
analysis
Complexity
Spectral
Soft-clustering
interface
Brain-computerElectroencephalogramConsciousnessconsciousnessDisordersConnectivityfrom:scadsfctanalysisComplexitySpectralSoft-clusteringinterface
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2Atypical fibroxanthoma and pleomorphic dermal sarcoma – gene expression analysis compared with undifferentiated cutaneous squamous cell carcinoma
I. Anders, C. Schimmelpfennig, K. Wiedemann, D. Löffler, C. Kämpf, C. Blumert, K. Reiche, M. Kunz, U. Anderegg, J. Simon and 1 other author(s). JDDG: Journal der Deutschen Dermatologischen Gesellschaft, 21 (5): 482–491 (April 2023)
2 months ago by @scads.ai
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cutaneous
undifferentiated
pleomorphic
sarcoma
carcinoma
fibroxanthoma
Atypical
from:scadsfct
cell
dermal
cutaneousundifferentiatedpleomorphicsarcomacarcinomafibroxanthomaAtypicalfrom:scadsfctcelldermal
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2RNAcode_Web – Convenient identification of evolutionary conserved protein coding regions
J. Anders, and P. Stadler. Journal of Integrative Bioinformatics, (August 2023)
2 months ago by @scads.ai
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identification
coding
regions
protein
from:scadsfct
RNAcode_Web
evolutionary
identificationcodingregionsproteinfrom:scadsfctRNAcode_Webevolutionary
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2Pattern Recognition
B. Andres, F. Bernard, D. Cremers, S. Frintrop, B. Goldlucke, and I. Ihrke (Eds.) Lecture notes in computer science Springer International Publishing, Cham, Switzerland, 1 edition, (September 2022)
3 months ago by @scads.ai
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from:scadsfct
topic_visualcomputing
from:scadsfcttopic_visualcomputing
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2A polyhedral study of lifted multicuts
B. Andres, S. Di Gregorio, J. Irmai, and J. Lange. Discrete Optimization, (2022)
3 months ago by @scads.ai
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from:scadsfct
topic_visualcomputing
from:scadsfcttopic_visualcomputing
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2BioDeepfuse: 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)
2 months ago by @scads.ai
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deep
RNA
non-coding
feature
learning
from:scadsfct
extraction
BioDeepfuse
classification
deepRNAnon-codingfeaturelearningfrom:scadsfctextractionBioDeepfuseclassification
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2Can 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)
2 months ago by @scads.ai
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Study
Learning
Computer
Data
Self-Supervised
from:scadsfct
Unlabelled
Vision.
Comparative
StudyLearningComputerDataSelf-Supervisedfrom:scadsfctUnlabelledVision.Comparative
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2An Open-Source Approach for Digital Prostate Cancer Histopathology: Bringing AI into Practice
M. Bauer, L. Schneider, M. Bernhardt, C. Augenstein, G. Kristiansen, and B. Franczyk. (2024)
2 months ago by @scads.ai
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Histopatholog
Cancer
Digital
AI
Prostate
from:scadsfct
Open-Source
HistopathologCancerDigitalAIProstatefrom:scadsfctOpen-Source
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2Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse
M. Bogdan. Louvain-la-Neuve (Belgium), Ciaco - i6doc.com, (2023)
a month ago by @scads.ai
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Singularity
AI
Boredom
from:scadsfct
SingularityAIBoredomfrom:scadsfct
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2Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse
M. Bogdan. XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja), Servizo de Publicacións da UDC, (September 2022)
a month ago by @scads.ai
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Learning
neural
algorithms
spiking
learning
from:scadsfct
plausible
networks
neurological
Learningneuralalgorithmsspikinglearningfrom:scadsfctplausiblenetworksneurological
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2Molecular characterization of Richter syndrome identifies de novo diffuse large B-cell lymphomas with poor prognosis
J. Broséus, S. Hergalant, J. Vogt, E. Tausch, M. Kreuz, A. Mottok, C. Schneider, C. Dartigeas, D. Roos-Weil, A. Quinquenel and 32 other author(s). Nature Communications, (January 2023)
2 months ago by @scads.ai
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de
Molecular
B-cell
syndrome
lymphomas
novo
Richter
from:scadsfct
characterization
deMolecularB-cellsyndromelymphomasnovoRichterfrom:scadsfctcharacterization
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2From modular decomposition trees to rooted median graphs
C. Bruckmann, P. Stadler, and M. Hellmuth. Discrete Applied Mathematics, (March 2022)
2 months ago by @scads.ai
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modular
graphs
median
rooted
decomposition
from:scadsfct
trees
modulargraphsmedianrooteddecompositionfrom:scadsfcttrees
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2Evolutionary conservation of secondary structures in the lncRNAs of plants
J. Corona-Gomez, P. Stadler, and S. Fernandez-Valverde. (August 2023)
2 months ago by @scads.ai
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lncRNAs
conservation
secondary
Evolutionary
structures
from:scadsfct
lncRNAsconservationsecondaryEvolutionarystructuresfrom:scadsfct
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2Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries
A. de Carvalho, R. Bonidia, J. Kong, M. Dauhajre, C. Struchiner, G. Goedert, P. Stadler, M. Walter, D. Sanches, T. Day and 9 other author(s). (2024)
2 months ago by @scads.ai
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sciences
Artificial
Intelligence
and
FOS
Computer
from:scadsfct
information
sciencesArtificialIntelligenceandFOSComputerfrom:scadsfctinformation
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2New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology
B. Derraz, G. Breda, C. Kaempf, F. Baenke, F. Cotte, K. Reiche, U. Köhl, J. Kather, D. Eskenazy, and S. Gilbert. npj Precision Oncology, (January 2024)
2 months ago by @scads.ai
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drug
oncology
thinking
therapies
precision
regulatory
from:scadsfct
AI-based
cell
drugoncologythinkingtherapiesprecisionregulatoryfrom:scadsfctAI-basedcell
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2Crossover Operators for Molecular Graphs with an Application to Virtual Drug Screening
N. Domschke, B. Schmidt, T. Gatter, R. Golnik, P. Eisenhuth, F. Liessmann, J. Meiler, and P. Stadler. (September 2024)
2 months ago by @scads.ai
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Screening
Operators
Molecular
Graphs
Virtual
from:scadsfct
Crossover
Drug
ScreeningOperatorsMolecularGraphsVirtualfrom:scadsfctCrossoverDrug
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2Accuracy of RNA Structure Prediction Depends on the Pseudoknot Grammar
D. Eggers, C. Höner zu Siederdissen, and P. Stadler. page 20–31. Springer Nature Switzerland, (2022)
2 months ago by @scads.ai
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DependsPseudoknot
RNA
Prediction
Grammar
from:scadsfct
Structure
DependsPseudoknotRNAPredictionGrammarfrom:scadsfctStructure
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2Evolution of DNA Methylation Across Ecdysozoa
J. Engelhardt, O. Scheer, P. Stadler, and S. Prohaska. Journal of Molecular Evolution, (January 2022)
2 months ago by @scads.ai
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imported
topic_mathfoundation
from:scadsfct
importedtopic_mathfoundationfrom:scadsfct
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publications (hide)68
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help for advanced sorting...
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2Sleep analysis in a CLIS patient using soft-clustering: a case study

2Application of soft-clustering to assess consciousness in a CLIS patient

2Assessing consciousness in patients with disorders of consciousness using soft-clustering

2Atypical fibroxanthoma and pleomorphic dermal sarcoma – gene expression analysis compared with undifferentiated cutaneous squamous cell carcinoma

2RNAcode_Web – Convenient identification of evolutionary conserved protein coding regions

2Pattern Recognition

2A polyhedral study of lifted multicuts

2BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.

2An Open-Source Approach for Digital Prostate Cancer Histopathology: Bringing AI into Practice

2Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse

2Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse

2Molecular characterization of Richter syndrome identifies de novo diffuse large B-cell lymphomas with poor prognosis

2From modular decomposition trees to rooted median graphs

2Evolutionary conservation of secondary structures in the lncRNAs of plants

2Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries

2New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

2Crossover Operators for Molecular Graphs with an Application to Virtual Drug Screening

2Accuracy of RNA Structure Prediction Depends on the Pseudoknot Grammar

2Evolution of DNA Methylation Across Ecdysozoa

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