Farah Kidwai-Khan
Data Scientist/Associate Research Scientist, Internal Medicine (General Medicine)DownloadHi-Res Photo
Cards
Appointments
General Internal Medicine
Primary
Contact Info
Yale University
12 MERLIN AVE
Sleepy Hollow, NY 10591
United States
About
Titles
Data Scientist/Associate Research Scientist, Internal Medicine (General Medicine)
Biography
Dr. Kidwai-Khan's is a senior Data Scientist whose work involves research related to applying theoretical data engineering and computer science knowledge to develop algorithms related to epidemiological and clinical research. This includes developing data modeling processes to create predictive modeling for tailored analysis related to epidemiological and clinical studies and development of complex databases and informatics tools in the domain of clinical and health services research.
Dr. Kidwai-Khan is an engineering management specialist. She is proficient in data management, programming and web development with experience in electronic health record and administrative data manipulation, analysis and data warehousing. She has developed several university wide critical applications and lead informatics related projects related to health services research studies at Yale and Veterans Health Administration.
Appointments
General Internal Medicine
Associate Research ScientistPrimaryBiomedical Informatics & Data Science
Associate Research ScientistSecondary
Other Departments & Organizations
Education & Training
- DEng
- George Washington University, Engineering (2022)
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Farah Kidwai-Khan's published research.
Publications Timeline
A big-picture view of Farah Kidwai-Khan's research output by year.
Amy Justice, MD, PhD
Christopher T Rentsch, PhD, FISPE
Cynthia Brandt, MD, MPH
Evelyn Hsieh, MD, PhD
Harini Bathulapalli
Julie Womack, PhD, CNM, FNP (BC)
9Publications
533Citations
Publications
2024
A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness
Kidwai-Khan F, Wang R, Skanderson M, Brandt C, Fodeh S, Womack J. A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness. Journal Of Biomedical Informatics 2024, 154: 104654. PMID: 38740316, PMCID: PMC11144439, DOI: 10.1016/j.jbi.2024.104654.Peer-Reviewed Original ResearchCitationsAltmetricConceptsArtificial intelligenceMachine learningNatural language processing techniquesRaw dataLife cycle of dataLanguage processing techniquesInput dataApplication of artificial intelligenceArtificial intelligence processesMachine learning algorithmsTransform raw dataNatural language processing algorithmsArtificial intelligence methodsApplication of AILanguage processing algorithmsLearning algorithmsIntelligent processingError rateIntelligence methodsData governanceProcessing algorithmsData expertiseAlgorithmic biasElectronic health record dataData frameworks
2022
Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care
Kidwai-Khan F, Rentsch C, Pulk R, Alcorn C, Brandt C, Justice A. Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care. Frontiers In Big Data 2022, 5: 1059088. PMID: 36458283, PMCID: PMC9705957, DOI: 10.3389/fdata.2022.1059088.Peer-Reviewed Original ResearchCitationsAltmetricConceptsK-Nearest NeighborSupport vector machinePreventable adverse eventsDecision support mechanismAdverse eventsCurrent medicationsExtreme gradient boostingPredictive modelingSoftware interfaceMachine learningVeterans AffairsData integrationF1 scoreLarge integrated healthcare systemNearest NeighborPatient's current medicationsVector machineOutpatient clinic visitsRandom forestDecision treeGradient boostingAUC scoreComplex treatment decisionsEHR dataIntegrated healthcare system
2021
HIV care using differentiated service delivery during the COVID‐19 pandemic: a nationwide cohort study in the US Department of Veterans Affairs
McGinnis KA, Skanderson M, Justice AC, Akgün KM, Tate JP, King JT, Rentsch CT, Marconi VC, Hsieh E, Ruser C, Kidwai‐Khan F, Yousefzadeh R, Erdos J, Park LS. HIV care using differentiated service delivery during the COVID‐19 pandemic: a nationwide cohort study in the US Department of Veterans Affairs. Journal Of The International AIDS Society 2021, 24: e25810. PMID: 34713585, PMCID: PMC8554215, DOI: 10.1002/jia2.25810.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsVeterans AffairsClinic visitsCohort studyVL testARV coverageCOVID-19 pandemicVeterans Aging Cohort StudyHIV healthcare deliveryNationwide cohort studyAging Cohort StudyViral load testsDifferentiated service deliveryHealthcare deliveryHIV careMost patientsPharmacy recordsVL testingCalendar periodHealthcare encountersOverall healthARVVirtual healthcareVirtual visitsVisitsService deliveryEarly initiation of prophylactic anticoagulation for prevention of coronavirus disease 2019 mortality in patients admitted to hospital in the United States: cohort study
Rentsch CT, Beckman JA, Tomlinson L, Gellad WF, Alcorn C, Kidwai-Khan F, Skanderson M, Brittain E, King JT, Ho YL, Eden S, Kundu S, Lann MF, Greevy RA, Ho PM, Heidenreich PA, Jacobson DA, Douglas IJ, Tate JP, Evans SJW, Atkins D, Justice AC, Freiberg MS. Early initiation of prophylactic anticoagulation for prevention of coronavirus disease 2019 mortality in patients admitted to hospital in the United States: cohort study. The BMJ 2021, 372: n311. PMID: 33574135, PMCID: PMC7876672, DOI: 10.1136/bmj.n311.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsProphylactic anticoagulationDay mortalityEarly initiationTherapeutic anticoagulationCohort studyInpatient mortalityHospital admissionAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionCoronavirus disease 2019 (COVID-19) mortalitySyndrome coronavirus 2 infectionCOVID-19History of anticoagulationSerious bleeding eventsCoronavirus 2 infectionHours of admissionObservational cohort studyRisk of deathCoronavirus disease 2019Real-world evidenceBleeding eventsSubcutaneous heparinHospital stayNationwide cohortCumulative incidence
2020
Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index
King JT, Yoon JS, Rentsch CT, Tate JP, Park LS, Kidwai-Khan F, Skanderson M, Hauser RG, Jacobson DA, Erdos J, Cho K, Ramoni R, Gagnon DR, Justice AC. Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index. PLOS ONE 2020, 15: e0241825. PMID: 33175863, PMCID: PMC7657526, DOI: 10.1371/journal.pone.0241825.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCharlson Comorbidity IndexVeterans Health AdministrationVACO IndexValidation cohortMedical administrative dataDevelopment cohortSARS-CoV-2 testing resultsMortality indexICD-10 diagnosis codesUS Veterans Health AdministrationSARS-CoV-2 infectionPre-existing medical conditionsCOVID-19 mortality riskPeripheral vascular diseaseCOVID-19 patientsCOVID-19 infectionCOVID-19 mortalitySARS-CoV-2Administrative dataLogistic regression modelsRace/ethnicityCohort subgroupsComorbidity indexOverall mortalityComorbid conditionsExtracting lung function measurements to enhance phenotyping of chronic obstructive pulmonary disease (COPD) in an electronic health record using automated tools
Akgün KM, Sigel K, Cheung KH, Kidwai-Khan F, Bryant AK, Brandt C, Justice A, Crothers K. Extracting lung function measurements to enhance phenotyping of chronic obstructive pulmonary disease (COPD) in an electronic health record using automated tools. PLOS ONE 2020, 15: e0227730. PMID: 31945115, PMCID: PMC6964890, DOI: 10.1371/journal.pone.0227730.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsMeSH KeywordsCohort StudiesData MiningElectronic Health RecordsForced Expiratory VolumeHealth Information SystemsHospitalizationHumansLungNatural Language ProcessingPulmonary Disease, Chronic ObstructiveSeverity of Illness IndexSoftwareUnited StatesUnited States Department of Veterans AffairsVeteransVital CapacityConceptsChronic obstructive pulmonary diseaseVeterans Aging Cohort StudyObstructive pulmonary diseaseFEV1 valuesPulmonary diseasePhenotyping of patientsPulmonary function testsAging Cohort StudyLung function measurementsElectronic health record dataHealth record dataStructured electronic health record dataPositive predictive valueElectronic health recordsAirflow obstructionChart reviewCohort studyExpiratory volumeCOPD phenotypesFunction testsVital capacityFEV1 measurementsDATA SOURCESPredictive valueClinical notes
2011
The Yale cTAKES extensions for document classification: architecture and application
Garla V, Re V, Dorey-Stein Z, Kidwai F, Scotch M, Womack J, Justice A, Brandt C. The Yale cTAKES extensions for document classification: architecture and application. Journal Of The American Medical Informatics Association 2011, 18: 614-620. PMID: 21622934, PMCID: PMC3168305, DOI: 10.1136/amiajnl-2011-000093.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsDocument classificationFeature extractionProcessing systemKnowledge Extraction SystemDocument classification systemClinical Text AnalysisDocument classifierFeature representationRadiology reportsOpen sourceClinical textText analysisTechnical challengesClassificationExtraction systemClassification systemRepresentationClassifierSemanticsSystemArchitectureRetrievalExtractionSyntaxExtensionValidity of diagnostic codes and liver‐related laboratory abnormalities to identify hepatic decompensation events in the Veterans Aging Cohort Study
Re V, Lim JK, Goetz MB, Tate J, Bathulapalli H, Klein MB, Rimland D, Rodriguez‐Barradas M, Butt AA, Gibert CL, Brown ST, Kidwai F, Brandt C, Dorey‐Stein Z, Reddy KR, Justice AC. Validity of diagnostic codes and liver‐related laboratory abnormalities to identify hepatic decompensation events in the Veterans Aging Cohort Study. Pharmacoepidemiology And Drug Safety 2011, 20: 689-699. PMID: 21626605, PMCID: PMC3131229, DOI: 10.1002/pds.2148.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsVeterans Aging Cohort StudyHepatic decompensation eventsPositive predictive valueHigh positive predictive valueLaboratory abnormalitiesAging Cohort StudyDecompensation eventsDiagnostic codesCohort studyHepatic decompensationVariceal hemorrhageOutpatient diagnostic codesChronic liver diseaseSpontaneous bacterial peritonitisImpact of medicationLiver dysfunctionBacterial peritonitisLiver diseaseMedical recordsOutpatient codesPredictive valueNatural historyAbnormalitiesEpidemiologic researchPatients
2010
Reporting Suicide: Impact on Suicidal Behaviour
Kidwai F. Reporting Suicide: Impact on Suicidal Behaviour. 2010, 173-190. DOI: 10.4135/9788132107972.n9.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
activity Frontiers in Artificial Intelligence
Journal ServiceAssociate EditorDetails2023 - Presentactivity Asian Network at Yale
Public ServiceCo-ChairDetails2022 - Presenthonor SWE – STEM recognition
National AwardSociety of Women EngineersDetails02/08/2022honor Women in STEM scholarship
Yale University AwardYale University Women’s OrganizationDetails06/01/2021honor SAE – Doctoral award scholarship
National AwardSociety of Automotive EngineersDetails03/01/2021
News
News
- July 27, 2022
New Appointments & Promotions Within Department of Internal Medicine
- September 02, 2021
New Award To Study Risk Model For Fractures in Persons With HIV
- April 28, 2021
59 Staff in Department Celebrate Service Milestones
- February 11, 2021
Use of Anticoagulants Within 24 Hours of Hospitalization Can Reduce Death in COVID-19 Patients
Get In Touch
Contacts
Mailing Address
Yale University
12 MERLIN AVE
Sleepy Hollow, NY 10591
United States