Peter Gershkovich, MD, MHA
Associate Professor of PathologyCards
Appointments
Additional Titles
Director, Section of Pathology Informatics and Cancer Data Science, Pathology
Contact Info
Appointments
Additional Titles
Director, Section of Pathology Informatics and Cancer Data Science, Pathology
Contact Info
Appointments
Additional Titles
Director, Section of Pathology Informatics and Cancer Data Science, Pathology
Contact Info
About
Copy Link
Titles
Associate Professor of Pathology
Director, Section of Pathology Informatics and Cancer Data Science, Pathology
Biography
Dr. Gershkovich joined Pathology Department in 2004 shortly after completing the NLM funded fellowship training at Yale Center for Medical Informatics. Since that time, he led the development of novel, cutting-edge software to mesh emerging technologies with existing commercial Laboratory Information System, robotic laboratory instruments, Digital Pathology equipment, and the Hospital EMR.
Dr. Gershkovich is interested in clinical systems engineering, information visualization, DNA sequencing analysis, NLP, and full-text search of clinical data. He is currently focusing on how to better assemble, compile, and deliver relevant information at the point where a clinical decision needs to be made.
The underlying philosophy in his software development is pragmatic reasoning which typically leads to the development of working systems that have meaningful impact on clinical care. The systems developed by his engineering group integrate into the daily workflow of the Pathology Department improving quality and efficiency of patient care and clinical operations.
At the onset of COVID epidemics, his group rapidly created and deployed a suite of software modules to support SARS-CoV-2 testing, further demonstrating that implanting software engineering activities in clinical services and translational research is essential for modern patient care.
This work is critical for patient safety, the integration and accuracy of new diagnostic techniques, continuous quality improvement, and impactful workflow reengineering in medicine.
Appointments
Pathology
Associate Professor on TermPrimary
Other Departments & Organizations
- Clinical Informatics Development
- Pathology
- Yale Center for Genomic Health
Education & Training
- Fellow
- Yale University, Yale Center for Medical Informatics (2002)
- MHA
- Suffolk University (1996)
- MD
- Altai State Medical University (1987)
Research
Copy Link
Overview
"Processing information faster and more efficiently, which today's technology can easily accomplish, is not sufficient. More intelligent processing, logical aggregation of information, synthesis, and analysis, and the development of knowledge systems that serve purposeful ends are needed." This is a quote from 1992 charter of NLM fellowship in applied informatics when it was just established remains even more relevant and critical today.
I have strong interest in rapid development methodologies and working on software that deals with systems integration and interoperability, supports Tumor DNA sequencing reporting, enables laboratory integration of digital pathology, and assists with analytics, information retrieval, and visualization.
ORCID
0000-0002-4432-4969
Research at a Glance
Yale Co-Authors
Publications Timeline
John Sinard, MD, PhD
Joanna Gibson, MD, PhD
David Rimm, MD, PhD
Angelique W. Levi, MD
Lajos Pusztai, MD, DPhil
Xavier Llor, MD, PhD
Publications
2025
Digital Pathology Standards: A Response to WG-26
Gershkovich P. Digital Pathology Standards: A Response to WG-26. Journal Of Pathology Informatics 2025, 19: 100510. PMID: 40977907, PMCID: PMC12444456, DOI: 10.1016/j.jpi.2025.100510.Peer-Reviewed Original ResearchWearing a fur coat in the summertime: Should digital pathology redefine medical imaging?
Gershkovich P. Wearing a fur coat in the summertime: Should digital pathology redefine medical imaging? Journal Of Pathology Informatics 2025, 18: 100450. PMID: 40979690, PMCID: PMC12446971, DOI: 10.1016/j.jpi.2025.100450.Peer-Reviewed Original ResearchCitationsAltmetricConceptsMedical imagesData streamsNIST SPTransport Layer SecuritySeparation of concernsFile Transfer ProtocolScalable Vector GraphicsLayer securityCryptographic hashCloud workflowsCloud computingSecurity requirementsEmbedding metadataMonolithic architectureDiverse data streamsInteroperability modelRigorous securityOrchestration logicHL7 FHIRVector graphicsCommunication protocolsModular softwareDICOM standardProprietary formatsTransfer protocolCost-effectiveness of Lynch Syndrome Screening in Colorectal Cancer: Universal Germline vs Sequential Screening
Ito S, Xicola R, Sra M, Potnis K, Singh V, Gershkovich P, Stites E, Gibson J, Krumholz H, Llor X, Goshua G. Cost-effectiveness of Lynch Syndrome Screening in Colorectal Cancer: Universal Germline vs Sequential Screening. Clinical Gastroenterology And Hepatology 2025, 23: 2328-2338.e9. PMID: 40315972, PMCID: PMC12354148, DOI: 10.1016/j.cgh.2025.03.006.Peer-Reviewed Original ResearchAltmetricConceptsLynch syndromeIncremental cost-effectiveness ratioGermline testingColorectal cancerProspective Lynch Syndrome DatabaseColorectal cancer probandsNational Cancer Institute's SurveillancePre-/post-interventionPreventing cancer incidenceLynch syndrome screeningEnd Results ProgramCost-effective interventionHealth system perspectiveCost-effectiveCancer incidenceQuality-adjusted life expectancyInstitute's SurveillanceResults ProgramProspective interventionStandard-of-careCost-effectiveness ratioLS testingCohort studyGenetic testingPrimary outcomeSoftware solution for integration of frozen section quality assurance into daily practice
Gibson J, Mutnick N, Gershkovich P, Sinard J. Software solution for integration of frozen section quality assurance into daily practice. American Journal Of Clinical Pathology 2025, 163: 794-802. PMID: 39838842, DOI: 10.1093/ajcp/aqae188.Peer-Reviewed Original ResearchConceptsPatient safetyImprove patient safetyQuality of careFS errorsClinical teamIncreased documentationSoftware solutionsSubspecialty expertisePathology facultyDaily practiceQuality assuranceShortened time intervalsCustom software solutionsInterventionReduce errorsResolution of errorsTechnical errorsCarePermanent diagnosisProgramFrozen sectionsPracticePhysical locationPathology laboratoryFaculty
2023
Organizational preparedness for the use of large language models in pathology informatics
Hart S, Hoffman N, Gershkovich P, Christenson C, McClintock D, Miller L, Jackups R, Azimi V, Spies N, Brodsky V. Organizational preparedness for the use of large language models in pathology informatics. Journal Of Pathology Informatics 2023, 14: 100338. PMID: 37860713, PMCID: PMC10582733, DOI: 10.1016/j.jpi.2023.100338.Peer-Reviewed Original ResearchCitationsAltmetricProceedings of the Association for Pathology Informatics Bootcamp 2022
Obstfeld A, Brodsky V, Carter A, Gershkovich P, Haymond S, Levy B, Sinard J, Sellers D, Stoffel M, Jackups R. Proceedings of the Association for Pathology Informatics Bootcamp 2022. Journal Of Pathology Informatics 2023, 14: 100331. PMID: 37705688, PMCID: PMC10495674, DOI: 10.1016/j.jpi.2023.100331.Peer-Reviewed Original ResearchCitations
2022
NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health
Lee P, Benz C, Blood P, Börner K, Campisi J, Chen F, Daldrup-Link H, De Jager P, Ding L, Duncan F, Eickelberg O, Fan R, Finkel T, Furman D, Garovic V, Gehlenborg N, Glass C, Heckenbach I, Joseph Z, Katiyar P, Kim S, Königshoff M, Kuchel G, Lee H, Lee J, Ma J, Ma Q, Melov S, Metis K, Mora A, Musi N, Neretti N, Passos J, Rahman I, Rivera-Mulia J, Robson P, Rojas M, Roy A, Scheibye-Knudsen M, Schilling B, Shi P, Silverstein J, Suryadevara V, Xie J, Wang J, Wong A, Niedernhofer L, Wang S, Anvari H, Balough J, Benz C, Bons J, Brenerman B, Evans W, Gerencser A, Gregory H, Hansen M, Justice J, Kapahi P, Murad N, O’Broin A, Pavone M, Powell M, Scott G, Shanes E, Shankaran M, Verdin E, Winer D, Wu F, Adams A, Blood P, Bueckle A, Cao-Berg I, Chen H, Davis M, Filus S, Hao Y, Hartman A, Hasanaj E, Helfer J, Herr B, Joseph Z, Molla G, Mou G, Puerto J, Quardokus E, Ropelewski A, Ruffalo M, Satija R, Schwenk M, Scibek R, Shirey W, Sibilla M, Welling J, Yuan Z, Bonneau R, Christiano A, Izar B, Menon V, Owens D, Phatnani H, Smith C, Suh Y, Teich A, Bekker V, Chan C, Coutavas E, Hartwig M, Ji Z, Nixon A, Dou Z, Rajagopal J, Slavov N, Holmes D, Jurk D, Kirkland J, Lagnado A, Tchkonia T, Abraham K, Dibattista A, Fridell Y, Howcroft T, Jhappan C, Montes V, Prabhudas M, Resat H, Taylor V, Kumar M, Suryadevara V, Cigarroa F, Cohn R, Cortes T, Courtois E, Chuang J, Davé M, Domanskyi S, Enninga E, Eryilmaz G, Espinoza S, Gelfond J, Kirkland J, Kuchel G, Kuo C, Lehman J, Aguayo-Mazzucato C, Meves A, Rani M, Sanders S, Thibodeau A, Tullius S, Ucar D, White B, Wu Q, Xu M, Yamaguchi S, Assarzadegan N, Cho C, Hwang I, Hwang Y, Xi J, Adeyi O, Aliferis C, Bartolomucci A, Dong X, DuFresne-To M, Ikramuddin S, Johnson S, Nelson A, Niedernhofer L, Revelo X, Trevilla-Garcia C, Sedivy J, Thompson E, Robbins P, Wang J, Aird K, Alder J, Beaulieu D, Bueno M, Calyeca J, Chamucero-Millaris J, Chan S, Chung D, Corbett A, Gorbunova V, Gowdy K, Gurkar A, Horowitz J, Hu Q, Kaur G, Khaliullin T, Lafyatis R, Lanna S, Li D, Ma A, Morris A, Muthumalage T, Peters V, Pryhuber G, Reader B, Rosas L, Sembrat J, Shaikh S, Shi H, Stacey S, Croix C, Wang C, Wang Q, Watts A, Gu L, Lin Y, Rabinovitch P, Sweetwyne M, Artyomov M, Ballentine S, Chheda M, Davies S, DiPersio J, Fields R, Fitzpatrick J, Fulton R, Imai S, Jain S, Ju T, Kushnir V, Link D, Ben Major M, Oh S, Rapp D, Rettig M, Stewart S, Veis D, Vij K, Wendl M, Wyczalkowski M, Craft J, Enninful A, Farzad N, Gershkovich P, Halene S, Kluger Y, VanOudenhove J, Xu M, Yang J, Yang M. NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health. Nature Aging 2022, 2: 1090-1100. PMID: 36936385, PMCID: PMC10019484, DOI: 10.1038/s43587-022-00326-5.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSenescence-associated secretory phenotypeSenescent cellsSecretory phenotypeMulti-omics datasetsStable growth arrestHuman lifespanDiverse rolesGrowth arrestProinflammatory senescence-associated secretory phenotypeHuman tissuesPhenotypeMetabolic changesCellsHuman healthLifespanPhysiological healthCommon Coordinate FrameworkSystems approach to enhance Lynch syndrome diagnosis through tumour testing
Singh V, Mezzacappa C, Gershkovich P, Di Giovanna J, Ganzak A, Gibson J, Sinard J, Xicola RM, Llor X. Systems approach to enhance Lynch syndrome diagnosis through tumour testing. Journal Of Medical Genetics 2022, 60: 533-539. PMID: 36115663, PMCID: PMC10020126, DOI: 10.1136/jmg-2022-108770.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsOriginal cohortColorectal adenocarcinomaLynch syndromeTumor testingGenetic testingPercentage of patientsProportion of patientsLynch syndrome diagnosisCG evaluationCancer genetic testingRace/ethnicityCRC testingCohort studyMMR immunohistochemistryLS diagnosisNew diagnosisMMR lossAcademic centersPatientsSyndrome diagnosisCohortCase identificationMethylation testingReferral differencesReferral mechanisms
2021
An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy
Perincheri S, Levi AW, Celli R, Gershkovich P, Rimm D, Morrow JS, Rothrock B, Raciti P, Klimstra D, Sinard J. An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy. Modern Pathology 2021, 34: 1588-1595. PMID: 33782551, PMCID: PMC8295034, DOI: 10.1038/s41379-021-00794-x.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMemorial Sloan-Kettering Cancer CenterCore biopsyPredictive valueDiagnostic accuracyProstate core needle biopsiesCore needle biopsySurgical pathology practiceNegative predictive valueProstate core biopsiesPositive predictive valueProstate cancer detectionStrong diagnostic accuracyPoor quality scansCancer detectionCancer CenterProstate biopsyLeading causeNeedle biopsyTransrectal approachProstate cancerProstatic adenocarcinomaProstate carcinomaBiopsyPathology practiceProstateMeasuring Faculty Effort: A Quantitative Approach That Aligns Personal and Institutional Goals in Pathology at Yale
Morrow JS, Gershkovich P, Gibson J, Gilshannon M, Kowalski D, Levi AW, Nguyen DX, Rimm DL, Xu ML, Sinard J. Measuring Faculty Effort: A Quantitative Approach That Aligns Personal and Institutional Goals in Pathology at Yale. Academic Pathology 2021, 8: 23742895211047985. PMID: 34646939, PMCID: PMC8504692, DOI: 10.1177/23742895211047985.Peer-Reviewed Original ResearchCitationsAltmetric
News
Copy Link
News
- October 23, 2025
Yale Pathology Develops AI Tool that Checks Records to Ensure Accuracy
- February 03, 2025
Migration to Epic Beaker Laboratory Information System Moves Forward with Onsite Visit from Epic Team
- September 25, 2024
Pathology Team Encouraged About Migration to Epic Beaker Laboratory Information System
- February 23, 2023
Digital Pathology Efforts Ramp Up as Thousands of Specimen Slides are Converted into Electronic Form at Yale
Get In Touch
Copy Link
Contacts
Locations
Department of Pathology
Academic Office
Brady Memorial Laboratory
310 Cedar Street, Ste BML B50C
New Haven, CT 06510
Appointments
203.785.2325