2023
POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021)
Suwalska A, Tobiasz J, Prazuch W, Socha M, Foszner P, Piotrowski D, Gruszczynska K, Sliwinska M, Walecki J, Popiela T, Przybylski G, Nowak M, Fiedor P, Pawlowska M, Flisiak R, Simon K, Zapolska G, Gizycka B, Szurowska E, Marczyk M, Cieszanowski A, Polanska J. POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021). Scientific Data 2023, 10: 348. PMID: 37268643, PMCID: PMC10236395, DOI: 10.1038/s41597-023-02229-5.Peer-Reviewed Original ResearchConceptsLung maskChest X-ray databaseChest X-ray imagesArtificial intelligence toolsCOVID-19 detectionX-ray databaseImage collectionImage databaseX-ray imagesIntelligence toolsSegmentation solutionSegmentation modelDiagnosis methodOriginal radiographsDatasetImagesCOVID-19 diagnosisDatabaseHealthcare systemMaskMedical assistanceSmall numberLung areaSetTool
2019
Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms
Zyla J, Marczyk M, Domaszewska T, Kaufmann SHE, Polanska J, Weiner J. Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms. Bioinformatics 2019, 35: 5146-5154. PMID: 31165139, PMCID: PMC6954644, DOI: 10.1093/bioinformatics/btz447.Peer-Reviewed Original ResearchConceptsReal-world datasetsEvaluation metricsCernoNovel algorithmReproducible scienceOnline implementationComputational timeFalse positive ratePractical reproducibilityFast algorithmSupplementary dataAlgorithmRelated dataNovel approachDatasetR packageEnrichment algorithmPositive rateMetricsImplementationEssential partGS sizeRepositoryPackage
2016
Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model
Marczyk M. Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model. Lecture Notes In Computer Science 2016, 9683: 284-294. DOI: 10.1007/978-3-319-38782-6_24.Peer-Reviewed Original ResearchParallel computing capabilitiesSpot detectionGaussian mixture modelGel imagesComputing capabilitiesAutomatic methodEfficient implementationComputational timeBest overall performanceMixture modelAbstract2D gel electrophoresisOverall performanceImagesTrue positionDetectionAlgorithmDatasetSoftwareImplementationCapabilityMethodThousandsAccurate estimates
2015
Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
Polanski A, Marczyk M, Pietrowska M, Widlak P, Polanska J. Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry. PLOS ONE 2015, 10: e0134256. PMID: 26230717, PMCID: PMC4521892, DOI: 10.1371/journal.pone.0134256.Peer-Reviewed Original ResearchConceptsGaussian mixture modelingMixture modelGaussian mixture modelPeak detectionProteomic mass spectraFeature extractionPartitioning algorithmEfficient algorithmSignal compressionSoftware packageAlgorithmMain ideaMixture modelingModeling approachModelingDatasetApplicationsDetectionPreliminary resultsDetection efficiencyProteomic datasetsMixture modeling approachModelDifferent typesHigh resolution