Kirill Veselkov
Assistant Professor AdjunctCards
About
Research
Publications
2024
Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes
Rita L, Southern J, Laponogov I, Higgins K, Veselkov K. Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes. Machine Learning And Knowledge Extraction 2024, 6: 2738-2752. DOI: 10.3390/make6040131.Peer-Reviewed Original ResearchEarly Detection of Macular Atrophy Automated Through 2D and 3D Unet Deep Learning
Wei W, Patel R, Laponogov I, Cordeiro M, Veselkov K. Early Detection of Macular Atrophy Automated Through 2D and 3D Unet Deep Learning. Bioengineering 2024, 11: 1191. DOI: 10.3390/bioengineering11121191.Peer-Reviewed Original ResearchAge-related macular degenerationOptical coherence tomographyMacular atrophyEarly detectionVolumetric optical coherence tomographyDice similarity coefficient scoreMacular degenerationCoherence tomographyFollow-upMonitoring patientsPatientsDetection of MAClinical decisionsAtrophyHuman gradersScoresLesionsTomographyEndpointDegenerationEyesIDENTIFYING NUTRITIONAL AND PHARMACOLOGICAL TARGETS FOR ALLEVIATING POLYCYSTIC OVARY SYNDROME USING GENOMIC-DRIVEN MACHINE LEARNING
Hanassab S, Southern J, Olabode A, Heinis T, Abbara A, Izzi-Engbeaya C, Veselkov K, Dhillo W. IDENTIFYING NUTRITIONAL AND PHARMACOLOGICAL TARGETS FOR ALLEVIATING POLYCYSTIC OVARY SYNDROME USING GENOMIC-DRIVEN MACHINE LEARNING. Fertility And Sterility 2024, 122: e414. DOI: 10.1016/j.fertnstert.2024.08.249.Peer-Reviewed Original ResearchFoundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation
Kerdegari H, Higgins K, Veselkov D, Laponogov I, Polaka I, Coimbra M, Pescino A, Leja M, Dinis-Ribeiro M, Kanonnikoff T, Veselkov K. Foundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation. Diagnostics 2024, 14: 1912. PMID: 39272697, PMCID: PMC11394237, DOI: 10.3390/diagnostics14171912.Peer-Reviewed Original ResearchUpper gastrointestinal (GI) cancerIntestinal metaplasiaGastric cancerGastrointestinal (GI) cancersImprove patient outcomesAccuracy of endoscopyCancer mortalityGlobal cancer mortalityArtificial intelligencePatient outcomesGC casesChronic inflammationRegular surveillanceGastric inflammationDeep learning modelsClinical practiceIntegration of artificial intelligenceIntegration of multimodal dataLarge-scale dataPathology image analysisEndoscopyCancerEarly detectionMultimodal dataPathologyP695 Untargeted proteomics analysis of baseline serum samples prior to biologic therapy initiation
Rauch M, Laponogov I, van Welsen I, Quinn A, Joustra V, Paulich H, Perez B, Ramkisoen R, Noble A, Satsangi J, D’Haens G, Williamson A, Veselkov K, van 't Wout A. P695 Untargeted proteomics analysis of baseline serum samples prior to biologic therapy initiation. Journal Of Crohn's And Colitis 2024, 18: i1316-i1317. DOI: 10.1093/ecco-jcc/jjad212.0825.Peer-Reviewed Original ResearchAnti-TNFa treatmentAnti-TNFaSerum proteomic profilesTreatment outcomesCrohn's diseaseTreatment responseNon-respondersCD patientsBiological drugsModerate to severe CDSerum collectionSustained clinical responseFirst-line therapyBaseline serum samplesProteomic profilingBiobanked serum samplesBiologic treatment outcomesSevere CD patientsSerum samplesBiologic treatment responseStandard of careSerum proteomic analysisClinical responseStratify patientsSevere CD