Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence
Hart GR, Yan V, Huang GS, Liang Y, Nartowt BJ, Muhammad W, Deng J. Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence. Frontiers In Artificial Intelligence 2020, 3: 539879. PMID: 33733200, PMCID: PMC7861326, DOI: 10.3389/frai.2020.539879.Peer-Reviewed Original ResearchAverage-risk womenEndometrial cancerRisk womenOvarian Cancer Screening TrialEndometrial cancer riskCancer Screening TrialPrimary care physiciansPopulation-based screeningCancer risk predictionHealth dataCare physiciansGynecologic oncologistsRisk stratificationDisease onsetPositive rateIndividual patientsCancer riskInvasive proceduresScreening TrialPersonal health dataEarly cancer detectionMortality rateEarly screeningFalse positive ratePrevious risk modelsPrescribed medical cannabis in women with gynecologic malignancies: A single-institution survey-based study
Webster EM, Yadav GS, Gysler S, McNamara B, Black J, Tymon-Rosario J, Zeybek B, Han C, Arkfeld CK, Andikyan V, Menderes G, Huang G, Azodi M, Silasi DA, Santin AD, Schwartz PE, Ratner ES, Altwerger G. Prescribed medical cannabis in women with gynecologic malignancies: A single-institution survey-based study. Gynecologic Oncology Reports 2020, 34: 100667. PMID: 33204797, PMCID: PMC7653050, DOI: 10.1016/j.gore.2020.100667.Peer-Reviewed Original ResearchTreatment-related symptomsGynecologic malignanciesMedical cannabisOpioid usePatient experienceBetter side effect profileDecrease opioid useGynecologic oncology populationPercent of patientsSide effect profileSubset of patientsBone painEligible patientsAbdominal painNeuropathic painRecurrent diseaseSymptom controlJoint painAdjunct therapyOncology populationEffect profileGynecologic oncologistsTraditional medicationsPainPatients