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1RostPaperBTW
C. Rost, A. Thor, and E. Rahm. Gesellschaft für Informatik, Bonn, (2019)
3 months ago by @scadsfct
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1On the expressive power of description logics with cardinality constraints on finite and infinite sets
F. Baader, and F. De Bortoli. Frontiers of Combining Systems, Springer International Publishing, Cham, (2019)
3 months ago by @scadsfct
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1Lifting the multimodality-fog in continuous multi-objective optimization
P. Kerschke, and C. Grimme. Natural Computing Series, Springer International Publishing, Cham, (2021)
3 months ago by @scadsfct
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1Weighted abstract Dialectical Frameworks: Extended and revised report
G. Brewka, J. Pührer, H. Strass, J. Wallner, and S. Woltran. (2018)
3 months ago by @scadsfct
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1Completeness and soundness guarantees for conjunctive SPARQL queries over RDF data sources with completeness statements
F. Darari, S. Rudolph, S. Razniewski, and W. Nutt. Semantic Web, 11 (3): 441--482 (2020)
3 months ago by @scadsfct
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1Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
M. Alshomary, T. Gurcke, S. Syed, P. Heinrich, M. Spliethöver, P. Cimiano, M. Potthast, and H. Wachsmuth. (2021)
3 months ago by @scadsfct
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1A user-centered approach to gamify the manual creation of training data for machine learning
S. Alaghbari, A. Mitschick, G. Blichmann, M. Voigt, and R. Dachselt. I-Com, 20 (1): 33--48 (April 2021)
3 months ago by @scadsfct
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1BioKEEN: a library for learning and evaluating biological knowledge graph embeddings
M. Ali, C. Hoyt, D. Domingo-Fernández, J. Lehmann, and H. Jabeen. Bioinformatics, 35 (18): 3538--3540 (September 2019)
3 months ago by @scadsfct
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1Gene losses in the common vampire bat illuminate molecular adaptations to blood feeding
M. Blumer, T. Brown, M. Freitas, A. Destro, J. Oliveira, A. Morales, T. Schell, C. Greve, M. Pippel, D. Jebb and 7 other author(s). (October 2021)
3 months ago by @scadsfct
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1IQA: Interactive query construction in semantic question answering systems
H. Zafar, M. Dubey, J. Lehmann, and E. Demidova. Web Semant., 64 (100586): 100586 (October 2020)
3 months ago by @scadsfct
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1Datalog-expressibility for monadic and Guarded Second-order Logic
M. Bodirsky, S. Knäuer, and S. Rudolph. (2020)
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1Neva-Extension Visualization for Argumentation Frameworks.
M. Yang, S. Gaggl, and S. Rudolph. COMMA, page 477--478. (2020)
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1HumanMetagenomeDB: a public repository of curated and standardized metadata for human metagenomes
J. Kasmanas, A. Bartholomäus, F. Corrêa, T. Tal, N. Jehmlich, G. Herberth, M. von Bergen, P. Stadler, A. Carvalho, and U. Nunes da Rocha. Nucleic Acids Res., 49 (D1): D743--D750 (January 2021)
3 months ago by @scadsfct
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1Formal ontology learning from English IS-A sentences
S. Dasgupta, A. Padia, G. Maheshwari, P. Trivedi, and J. Lehmann. (2018)
3 months ago by @scadsfct
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1Squerall: Virtual ontology-based access to heterogeneous and large data sources
M. Mami, D. Graux, S. Scerri, H. Jabeen, S. Auer, and J. Lehmann. Lecture Notes in Computer Science, Springer International Publishing, Cham, (2019)
3 months ago by @scadsfct
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1A testing environment for continuous colormaps
P. Nardini, M. Chen, R. Bujack, M. Bottinger, and G. Scheuermann. IEEE Trans. Vis. Comput. Graph., 27 (2): 1043--1053 (February 2021)
3 months ago by @scadsfct
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1A visualization authoring model for Post-WIMP interfaces
M. Satkowski, W. Luo, and R. Dachselt. (2021)
3 months ago by @scadsfct
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1Visualization of statistical information in concept lattice diagrams
J. Klimpke, and S. Rudolph. Formal Concept Analysis, Springer International Publishing, Cham, (2021)
3 months ago by @scadsfct
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1Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness
K. Khatib, M. Völske, S. Syed, N. Kolyada, and B. Stein. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, (2020)
3 months ago by @scadsfct
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1Better a Microbenchmark on a Cluster than a User at the Office: Flink Cluster Benchmarking
D. Reichelt, L. Meyer, and S. Kühne. Softwaretechnik-Trends Band 39, Heft 3, page 52--54. Bonn, Gesellschaft für Informatik e.V., (2019)
3 months ago by @scadsfct
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topic_lifescience
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1Interview with Gerhard brewka
G. Brewka, T. Schaub, and S. Woltran. KI - Künstl. Intell., 32 (2-3): 219--221 (August 2018)
3 months ago by @scadsfct
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1Machine learning studies of non-coding RNAs based on artificially constructed training data
M. Costa, J. Oliveira, W. C. da Silva, R. Sen, J. Fallmann, P. Stadler, and M. Walter. Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, SCITEPRESS - Science and Technology Publications, (2021)
3 months ago by @scadsfct
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1The node weight dependent traveling salesperson problem
J. Bossek, K. Casel, P. Kerschke, and F. Neumann. Proceedings of the 2020 Genetic and Evolutionary Computation Conference, New York, NY, USA, ACM, (June 2020)
3 months ago by @scadsfct
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1How to feed the squerall with RDF and other data nuts?
M. Mami, D. Graux, S. Scerri, H. Jabeen, S. Auer, and J. Lehmann. (2019)
3 months ago by @scadsfct
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1Missing velocity in dynamic obstacle avoidance based on Deep Reinforcement Learning
F. Hart, M. Waltz, and O. Okhrin. (2021)
3 months ago by @scadsfct
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1125-129 10.1055/a-1030-3232 gockel Ines I Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Jansen-winkeln Boris B Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Sucher Robert R Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Rayes Nada N Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Thieme René R Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Moulla Yusef Y Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Niebisch Stefan S Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Rademacher Sebastian S Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Seehofer Daniel D Klinik und poliklinik für viszeral-, transplantations-, thorax- und gefäßchirurgie, Universitätsklinikum Leipzig AöR, Deutschland. Schierle Katrin K Institut für pathologie, Universitätsklinikum Leipzig AöR, Deutschland. Bläker Hendrik H Institut für pathologie, Universitätsklinikum Leipzig AöR, Deutschland. Neumuth Thomas T innovation center computer assisted surgery (ICCAS), Universität Leipzig, Deutschland. Melzer Andreas A innovation center computer assisted surgery (ICCAS), Universität Leipzig, Deutschland. Maktabi Marianne M innovation center computer assisted surgery (ICCAS), Universität Leipzig, Deutschland. Köhler Hannes H innovation center computer assisted surgery (ICCAS), Universität Leipzig, Deutschland. Chalopin Claire C innovation center computer assisted surgery (ICCAS), Universität Leipzig, Deutschland. Ger journal article hyperspektral-imaging (HSI) -- eine verlässliche gewebedifferenzierung? 2020 04 08
I. Gockel, B. Jansen-Winkeln, R. Sucher, N. Rayes, R. Thieme, Y. Moulla, S. Niebisch, S. Rademacher, D. Seehofer, K. Schierle and 6 other author(s). Zentralbl. Chir., 145 (2): 125--129 (April 2020)
3 months ago by @scadsfct
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topic_lifescience
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1Argumentation-based explanations for answer sets using ADF
L. Rolf, G. Kern-Isberner, and G. Brewka. Logic Programming and Nonmonotonic Reasoning, Springer International Publishing, Cham, (2019)
3 months ago by @scadsfct
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1EvoChef: Show me what to cook! Artificial evolution of culinary arts
H. Jabeen, N. Tahara, and J. Lehmann. Computational Intelligence in Music, Sound, Art and Design, Springer International Publishing, Cham, (2019)
3 months ago by @scadsfct
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1Compatibility of partitions with trees, hierarchies, and split systems
M. Hellmuth, D. Schaller, and P. Stadler. (2021)
3 months ago by @scadsfct
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1GofCopula: Goodness-of-fit tests for copulae
O. Okhrin, S. Trimborn, and M. Waltz. SSRN Electron. J., (2020)
3 months ago by @scadsfct
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1Why reinvent the wheel
K. Singh, C. Lange, M. Vidal, J. Lehmann, S. Auer, A. Radhakrishna, A. Both, S. Shekarpour, I. Lytra, R. Usbeck and 3 other author(s). Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, New York, New York, USA, ACM Press, (2018)
3 months ago by @scadsfct
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1Description logics with concrete domains and general concept inclusions revisited
F. Baader, and J. Rydval. Automated Reasoning, Springer International Publishing, Cham, (2020)
3 months ago by @scadsfct
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1MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes
M. Nata'ala, A. Avila Santos, J. Coelho Kasmanas, A. Bartholomäus, J. Saraiva, S. Godinho Silva, T. Keller-Costa, R. Costa, N. Gomes, A. Ponce de Leon Ferreira de Carvalho and 3 other author(s). Environ. Microbiome, 17 (1): 57 (November 2022)
3 months ago by @scadsfct
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topic_mathfoundation
Database;
Marine
Metadata;
Metagenomics;
Microbial
ecology
microbiomes;
topic_lifescience
topic_mathfoundationDatabase;MarineMetadata;Metagenomics;Microbialecologymicrobiomes;topic_lifescience
(0)
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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)
3 months ago by @scadsfct
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topic_lifescience
artificial
deep
gene
image
immune
intelligence;
learning;
pathology;
signatures;
slide
whole
topic_lifescienceartificialdeepgeneimageimmuneintelligence;learning;pathology;signatures;slidewhole
(0)
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1Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review
L. Schneider, S. Laiouar-Pedari, S. Kuntz, E. Krieghoff-Henning, A. Hekler, J. Kather, T. Gaiser, S. Fröhling, and T. Brinker. Eur. J. Cancer, (January 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
Biomarker
Cancer;
Convolutional
Multimodal
Omics
fusion;
identification;
networks;
neural
topic_lifescienceBiomarkerCancer;ConvolutionalMultimodalOmicsfusion;identification;networks;neural
(0)
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1Uncertainty estimation in medical image classification: Systematic review
A. Kurz, K. Hauser, H. Mehrtens, E. Krieghoff-Henning, A. Hekler, J. Kather, S. Fröhling, C. von Kalle, and T. Brinker. JMIR Med. Inform., 10 (8): e36427 (August 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
calibration;
classification;
deep
detection;
estimation
image
imaging;
learning;
medical
network
out-of-distribution
uncertainty
topic_lifesciencecalibration;classification;deepdetection;estimationimageimaging;learning;medicalnetworkout-of-distributionuncertainty
(0)
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1Explainable artificial intelligence in skin cancer recognition: A systematic review
K. Hauser, A. Kurz, S. Haggenmüller, R. Maron, C. von Kalle, J. Utikal, F. Meier, S. Hobelsberger, F. Gellrich, M. Sergon and 23 other author(s). Eur. J. Cancer, (May 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
Artificial
Dermatology;
Man-machine
Skin
Systematic
intelligence;
neoplasms;
review
systems;
topic_lifescienceArtificialDermatology;Man-machineSkinSystematicintelligence;neoplasms;reviewsystems;
(0)
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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)
3 months ago by @scadsfct
show all tags
topic_lifescience
Artificial
Computational
Convolutional
Learning;
Multiple-Instance
Vision
Weakly-supervised
deep
intelligence;
learning
networks;
neural
pathology;
transformers;
topic_lifescienceArtificialComputationalConvolutionalLearning;Multiple-InstanceVisionWeakly-superviseddeepintelligence;learningnetworks;neuralpathology;transformers;
(0)
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1Nestin as a diagnostic and prognostic marker for combined hepatocellular-cholangiocarcinoma
J. Calderaro, L. Di Tommaso, P. Maillé, A. Beaufrère, C. Nguyen, L. Heij, V. Gnemmi, R. Graham, F. Charlotte, S. Chartier and 66 other author(s). J. Hepatol., 77 (6): 1586--1597 (December 2022)
3 months ago by @scadsfct
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topic_lifescience
cancer;
carcinoma;
cholangiocarcinoma;
combined
hepatocellular
hepatocellular-cholangiocarcinoma;
liver;
nestin
topic_lifesciencecancer;carcinoma;cholangiocarcinoma;combinedhepatocellularhepatocellular-cholangiocarcinoma;liver;nestin
(0)
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1Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology
P. Schrammen, N. Ghaffari Laleh, A. Echle, D. Truhn, V. Schulz, T. Brinker, H. Brenner, J. Chang-Claude, E. Alwers, A. Brobeil and 9 other author(s). J. Pathol., 256 (1): 50--60 (January 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
Lynch
artificial
cancer;
colorectal
computational
deep
digital
instability
intelligence;
learning;
microsatellite
pathology;
syndrome;
topic_lifescienceLynchartificialcancer;colorectalcomputationaldeepdigitalinstabilityintelligence;learning;microsatellitepathology;syndrome;
(0)
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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)
3 months ago by @scadsfct
show all tags
topic_lifescience
AI;
LNM
adipose
and
artificial
biomarker;
bowel
cancer;
colorectal
deep
digital
early
inflamed
intelligence;
learning;
metastasis;
new
pT1
pT2
pathology;
prediction
predictive
tissue;
topic_lifescienceAI;LNMadiposeandartificialbiomarker;bowelcancer;colorectaldeepdigitalearlyinflamedintelligence;learning;metastasis;newpT1pT2pathology;predictionpredictivetissue;
(0)
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1Artificial intelligence to identify genetic alterations in conventional histopathology
D. Cifci, S. Foersch, and J. Kather. J. Pathol., 257 (4): 430--444 (July 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
analysis;
artificial
biomarker;
image
intelligence;
oncology
precision
topic_lifescienceanalysis;artificialbiomarker;imageintelligence;oncologyprecision
(0)
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1Model soups improve performance of dermoscopic skin cancer classifiers
R. Maron, A. Hekler, S. Haggenmüller, C. von Kalle, J. Utikal, V. Müller, M. Gaiser, F. Meier, S. Hobelsberger, F. Gellrich and 23 other author(s). Eur. J. Cancer, (September 2022)
3 months ago by @scadsfct
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topic_lifescience
Artificial
Calibration;
Deep
Dermatology;
Ensembles;
Generalisation;
Melanoma;
Model
Nevus;
Robustness
intelligence;
learning;
soups;
topic_lifescienceArtificialCalibration;DeepDermatology;Ensembles;Generalisation;Melanoma;ModelNevus;Robustnessintelligence;learning;soups;
(0)
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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)
3 months ago by @scadsfct
show all tags
topic_lifescience
Artificial
Bladder
Deep
FGFR3
Molecular
cancer;
factor
fibroblast
for
growth
intelligence;
learning;
mutations;
receptor
testing
therapy
topic_lifescienceArtificialBladderDeepFGFR3Molecularcancer;factorfibroblastforgrowthintelligence;learning;mutations;receptortestingtherapy
(0)
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1The future of artificial intelligence in digital pathology - results of a survey across stakeholder groups
C. Heinz, A. Echle, S. Foersch, A. Bychkov, and J. Kather. Histopathology, 80 (7): 1121--1127 (June 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
artificial
digital
intelligence;
pathology;
survey
topic_lifescienceartificialdigitalintelligence;pathology;survey
(0)
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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)
3 months ago by @scadsfct
show all tags
topic_lifescience
AI,
Artificial
CNN,
Communications
DICOM,
Diagnosis;
Digital
HCC,
Imaging
Individual
ML,
MVI,
Medicine;
NAFLD,
NASH,
Prognosis
Reporting
TACE,
TRIPOD,
Transparent
WSIs,
a
and
artificial
carcinoma;
chemoembolisation;
convolutional
data
deep
diagnostic
disease;
fatty
for
hepatocellular
images;
imaging;
in
integration
intelligence;
invasion;
learning;
liver
machine
microvascular
model
multimodal
multivariable
network;
neural
non-alcoholic
of
or
prediction
slide
steatohepatitis;
support
system;
transarterial
whole
topic_lifescienceAI,ArtificialCNN,CommunicationsDICOM,Diagnosis;DigitalHCC,ImagingIndividualML,MVI,Medicine;NAFLD,NASH,PrognosisReportingTACE,TRIPOD,TransparentWSIs,aandartificialcarcinoma;chemoembolisation;convolutionaldatadeepdiagnosticdisease;fattyforhepatocellularimages;imaging;inintegrationintelligence;invasion;learning;livermachinemicrovascularmodelmultimodalmultivariablenetwork;neuralnon-alcoholicoforpredictionslidesteatohepatitis;supportsystem;transarterialwhole
(0)
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1Structural comparative modeling of multi-domain F508del CFTR
E. McDonald, H. Woods, S. Smith, M. Kim, C. Schoeder, L. Plate, and J. Meiler. Biomolecules, 12 (3): 471 (March 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
VX-809;
chaperones;
comparative
computational
cystic
discovery
disease;
drug
fibrosis;
folding
modeling;
pharmacological
protein
structure-based
topic_lifescienceVX-809;chaperones;comparativecomputationalcysticdiscoverydisease;drugfibrosis;foldingmodeling;pharmacologicalproteinstructure-based
(0)
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1Modeling of protein conformational changes with Rosetta guided by limited experimental data
D. Sala, D. Del Alamo, H. Mchaourab, and J. Meiler. Structure, 30 (8): 1157--1168.e3 (August 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
EPR
Rosetta;
biology;
changes;
conformational
dynamics;
integrative
modeling;
molecular
protein
refinement
spectroscopy;
structural
structure
topic_lifescienceEPRRosetta;biology;changes;conformationaldynamics;integrativemodeling;molecularproteinrefinementspectroscopy;structuralstructure
(0)
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1Veratridine can bind to a site at the mouth of the channel pore at human cardiac sodium channel NaV1.5
A. Gulsevin, A. Glazer, T. Shields, B. Kroncke, D. Roden, and J. Meiler. Int. J. Mol. Sci., 23 (4): 2225 (February 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
Rosetta;
SCN5A;
cardiac
channels
channels;
docking;
electrophysiology;
molecular
mutagenesis;
site-directed
sodium
toxins;
veratridine;
voltage-gated
topic_lifescienceRosetta;SCN5A;cardiacchannelschannels;docking;electrophysiology;molecularmutagenesis;site-directedsodiumtoxins;veratridine;voltage-gated
(0)
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1The human antibody sequence space and structural design of the V, J regions, and CDRH3 with Rosetta
S. Schmitz, E. Schmitz, J. Crowe, Jr, and J. Meiler. MAbs, 14 (1): 2068212 (January 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
Human-likeness;
HumanizationABBREVIATIONS
antibody
biostatistics;
design;
immunome
repertoire;
rosetta;
topic_lifescienceHuman-likeness;HumanizationABBREVIATIONSantibodybiostatistics;design;immunomerepertoire;rosetta;
(0)
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