Kirill Veselkov
Assistant Professor AdjunctCards
About
Research
Publications
2025
The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations
Higgins K, Nyssen O, Southern J, Laponogov I, Veselkov D, Gisbert J, Kanonnikoff T, Veselkov K. The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations. Nature Communications 2025, 16: 6472. PMID: 40659612, PMCID: PMC12259899, DOI: 10.1038/s41467-025-61329-5.Peer-Reviewed Original ResearchConceptsNon-bismuth quadruple therapyH. pyloriBismuth-based therapyProspective clinical validationOptimal treatment strategyGastric cancer burdenDeep Q-learningHelicobacter pylori managementAntibiotic allergyQuadruple therapyOptimal therapyPotential of AIConcurrent medicationsHarness artificial intelligencePre-treatment indicatorsClinical decision-makingEuropean RegistryTreatment strategiesPatient characteristicsQ-learningGastric cancerHp-EuRegTreatment selectionTherapyTreatment recommendationsA multi-centre, stratified, open, randomized, comparator-controlled, parallel group phase II trial comparing adjuvant treatment with 177Lu-DOTATATE to standard of care in patients after resection of neuroendocrine liver metastases (NELMAS).
Frilling A, Baum R, Veselkov K, Martinez Del Peral E, Martinez M, Lovelle M, Wu J, Park S, Clift A, Eccles A, Hubber J, Wasan H, Modlin I. A multi-centre, stratified, open, randomized, comparator-controlled, parallel group phase II trial comparing adjuvant treatment with 177Lu-DOTATATE to standard of care in patients after resection of neuroendocrine liver metastases (NELMAS). Journal Of Clinical Oncology 2025, 43 DOI: 10.1200/jco.2025.43.16_suppl.tps4225.Peer-Reviewed Original ResearchGastro-entero-pancreatic neuroendocrine tumorsNeuroendocrine liver metastasesDisease-free survivalStandard of careGastro-entero-pancreaticResection of LMNeuroendocrine tumorsLu-DOTATATEOverall survivalTumor recurrenceLiver resectionAdjuvant treatmentResection of neuroendocrine liver metastasesEarly detection of recurrent diseaseEfficacy of adjuvant therapyPeptide receptor radionuclide therapyDetection of recurrent diseaseDisease-free survival probabilityAssociated with favorable overall survivalStandard of care armAdjuvant treatment conceptsGa-DOTATATE PET/CTLiver-directed therapiesMacroscopic complete resectionProspective open-label
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. PMID: 39768009, PMCID: PMC11726850, 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 ResearchLeveraging genomic-based machine learning to discover bioactive molecules that alleviate symptoms of polycystic ovary syndrome
Olabode A, Hanassab S, Southern J, Izzi-Engbeaya C, Heinis T, Abbara A, Veselkov K, Dhillo W. Leveraging genomic-based machine learning to discover bioactive molecules that alleviate symptoms of polycystic ovary syndrome. Endocrine Abstracts 2024 DOI: 10.1530/endoabs.104.p190.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: i1306-i1307. 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