2025
Artificial Intelligence Algorithm Predicts Response to Immune Checkpoint Inhibitors.
Fa'ak F, Coudray N, Jour G, Ibrahim M, Illa-Bochaca I, Qiu S, Claudio Quiros A, Yuan K, Johnson D, Rimm D, Weber J, Tsirigos A, Osman I. Artificial Intelligence Algorithm Predicts Response to Immune Checkpoint Inhibitors. Clinical Cancer Research 2025 PMID: 40553453, DOI: 10.1158/1078-0432.ccr-24-3720.Peer-Reviewed Original ResearchResponse to ICIImmune checkpoint inhibitorsMetastatic melanoma cohortCheckpoint inhibitorsMelanoma cohortMelanoma treated with immune checkpoint inhibitorsBiomarkers of ICI responseImmune checkpoint inhibitor useImmune checkpoint inhibitor treatmentCohort of melanoma patientsLow tumor stroma ratioProgression-free survivalTumor-stroma ratioSignificant adverse eventsArea under the curvePatient overall survivalMetastatic settingUnresectable melanomaEpithelioid histologyICI responseMelanoma patientsMetastatic melanomaOverall survivalPatient survivalTumor featuresArtificial intelligence-assisted detection of nasopharyngeal carcinoma on endoscopic images: a national, multicentre, model development and validation study
Shi Y, Li Z, Wang L, Wang H, Liu X, Gu D, Chen X, Liu X, Gong W, Jiang X, Li W, Lin Y, Liu K, Luo D, Peng T, Peng X, Tong M, Zheng H, Zhou X, Wu J, El Fakhri G, Chang M, Liao J, Li J, Wang D, Ye J, Qu S, Jiang W, Liu Q, Sun X, Zheng Y, Yu H. Artificial intelligence-assisted detection of nasopharyngeal carcinoma on endoscopic images: a national, multicentre, model development and validation study. The Lancet Digital Health 2025, 100869. PMID: 40544083, DOI: 10.1016/j.landig.2025.03.001.Peer-Reviewed Original ResearchArea under the curveNasopharyngeal carcinomaEndoscopic imagesReal-world environmentDeep learning algorithmsDeep learning systemBenign hyperplasiaNormal nasopharynxShanghai Municipal Key Clinical SpecialtyLearning algorithmsMalignant imagesSkull base tumorsDetection of nasopharyngeal carcinomaLearning systemAI modelsIncidence of nasopharyngeal carcinomaPrimary hospitalsDiagnostic capabilitiesNasopharyngeal carcinoma diagnosisDiagnostic challengeImaging manifestationsCarcinoma diagnosisCarcinomaDiagnostic accuracyEndoscopic examinationUsing vascular biomarkers to assess heart failure event risk in hospitalized patients with and without AKI
Shi A, Andrawis A, Biswas A, Wilson F, Obeid W, Philbrook H, Go A, Ikizler T, Siew E, Chinchilli V, Hsu C, Garg A, Reeves W, Prince D, Bhatraju P, Coca S, Liu K, Kimmel P, Kaufman J, Wurfel M, Himmelfarb J, Parikh C, Mansour S. Using vascular biomarkers to assess heart failure event risk in hospitalized patients with and without AKI. BMC Nephrology 2025, 26: 271. PMID: 40457292, PMCID: PMC12131712, DOI: 10.1186/s12882-025-04169-1.Peer-Reviewed Original ResearchConceptsArea under the curveRisk of HF eventsHeart failureHF eventsHospitalized patientsPrediction of HFVascular biomarkersClinical modelHigher risk of HF eventsPrediction of HF eventsLevels of injury markersRates of heart failureDormant phenotypeAssociated with higher riskCox regression analysisHeart failure eventsCardiovascular disease risk factorsPost-hospitalizationDisease risk factorsSerum creatinineAKI patientsStratify patientsInjury markersLung diseaseClinical centersComparative Analysis of RT-PCR and a Colloidal Gold Immunochromatographic Assay for SARS-CoV-2 Detection
Li H, Liu D, Zhou Q, Rodriguez G, Pietz H, Singh V, Konadu E, James K, Lui C, Shao M, Chen J, Schreiner A, Urban C, Truong J, Prasad N, Rodgers W. Comparative Analysis of RT-PCR and a Colloidal Gold Immunochromatographic Assay for SARS-CoV-2 Detection. Diagnostics 2025, 15: 1362. PMID: 40506934, PMCID: PMC12154499, DOI: 10.3390/diagnostics15111362.Peer-Reviewed Original ResearchGold immunochromatographic assayColloidal gold immunochromatographic assaySARS-CoV-2 detectionRT-PCRLarge-scale screeningSARS-CoV-2Immunochromatographic assayResource-limited settingsAnalysis of RT-PCRRT-PCR resultsReceiver operating characteristic curve analysisProlonged turnaround timeRT-PCR Ct valuesCalculate area under the curveArea under the curveCharacteristic curve analysisPoint-of-care applicationsPerformance of RT-PCRAlternative diagnostic toolAssayClinical parametersRT-PCR testEarly detection effortsDiagnostic performanceCurve analysisFDG-PET intensity normalization improves radiomics- based survival prediction in oropharyngeal cancer patients: a comparison of the SUV with alternative normalization techniques.
Payabvash S, Sharaf K, Zeevi T, Gross M, Mahajan A, Kann B, Judson B, Schreier A, Krenn J, Prasad M, Burtness B, Aboian M, Canis M, Baumeister P, Reichel C, Haider S. FDG-PET intensity normalization improves radiomics- based survival prediction in oropharyngeal cancer patients: a comparison of the SUV with alternative normalization techniques. American Journal Of Neuroradiology 2025, ajnr.a8836. PMID: 40379456, DOI: 10.3174/ajnr.a8836.Peer-Reviewed Original ResearchOropharyngeal squamous cell carcinomaStandardized uptake valueSquamous cell carcinomaFDG-PETRadiomic featuresPET featuresOncological outcomesLentiform nucleusCell carcinomaUptake valuePrognostic value of radiomics featuresC-indexOropharyngeal squamous cell carcinoma patientsValue of radiomic featuresProgression-free survivalOropharyngeal cancer patientsUnivariate Cox regression modelPredicting oncological outcomesRandom survival forestArea under the curveHarrell's concordance indexIndividual radiomics featuresStandardized uptake ratioHarrell's C-indexCox regression modelsAcoustic-based machine learning approaches for depression detection in Chinese university students
Wei Y, Qin S, Liu F, Liu R, Zhou Y, Chen Y, Xiong X, Zheng W, Ji G, Meng Y, Wang F, Zhang R. Acoustic-based machine learning approaches for depression detection in Chinese university students. Frontiers In Public Health 2025, 13: 1561332. PMID: 40443925, PMCID: PMC12119278, DOI: 10.3389/fpubh.2025.1561332.Peer-Reviewed Original ResearchConceptsPatient Health Questionnaire-9Mel-frequency cepstral coefficientsLinear discriminant analysisMachine learning algorithmsAcoustic featuresLearning algorithmsIdentification of depressionMonitoring of depressionCross-sectional studyGlobal public health problemSHapley Additive exPlanationsDepression screeningSelf-report methodsPublic health problemIdentifying depressionLinear discriminant analysis modelDepression assessmentSupport vector classificationAutomated identificationMachine learning approachArea under the curveHealth problemsOpenSMILE toolkitLogistic regressionCepstral coefficientsDetection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence.
Hillis J, Bizzo B, Mercaldo S, Ghatak A, MacDonald A, Halle M, Schultz A, L'Italien E, Tam V, Bart N, Moura F, Awad A, Bargiela D, Dagen S, Toland D, Blood A, Gross D, Jering K, Lopes M, Marston N, Nauffal V, Dreyer K, Scirica B, Ho C. Detection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence. Circulation Heart Failure 2025, e012667. PMID: 40365710, DOI: 10.1161/circheartfailure.124.012667.Peer-Reviewed Original ResearchHypertrophic cardiomyopathyDetection of hypertrophic cardiomyopathyAssociated with significant morbidityPredictive valueNegative predictive valueArea under the curvePositive predictive valueSudden cardiac deathSignificant morbidityChart reviewCardiac deathScreening electrocardiogramDiagnostic codesCardiac imagingClinical expertisePopulation prevalenceBinary outcomesCardiomyopathyElectrocardiogramDiagnosisImprove detectionPrevalenceElectrocardiogram featuresCharacterizing the ADPKD-IFT140 Phenotypic Signature with Deep Learning and Advanced Imaging Biomarkers
Ghanem A, Debeh F, Borghol A, Zagorec N, Tapia A, Smith B, Paul S, Basit A, AlKhatib B, Nader N, Antoun M, Gregory A, Yang H, Schauer R, Dahl N, Hanna C, Torres V, Kline T, Harris P, Gall E, Chebib F. Characterizing the ADPKD-IFT140 Phenotypic Signature with Deep Learning and Advanced Imaging Biomarkers. Kidney International Reports 2025 DOI: 10.1016/j.ekir.2025.04.062.Peer-Reviewed Original ResearchArea under the curveHeight-adjusted total kidney volumeAutosomal dominant polycystic kidney diseaseEstimated glomerular filtrationDisease-causing variantsDevelopment cohortAdvanced imaging biomarkersTotal kidney volumeDominant polycystic kidney diseaseRetrospective cohort studyPolycystic kidney diseaseClinical presentationCyst volumeKidney volumeCyst diameterCystic indexDiverse clinical settingsLiver cystsCohort studyExternal cohortKidney diseaseLarge cystsInternational cohortGlomerular filtrationPatientsSelection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real‐world data and machine learning model algorithms
Tang H, Xia H, Sun N, Hernandez P, Wang M, Adeniran A, Cai G. Selection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real‐world data and machine learning model algorithms. Cancer Cytopathology 2025, 133: e70018. PMID: 40289395, DOI: 10.1002/cncy.70018.Peer-Reviewed Original ResearchConceptsMachine learning algorithmsReal-world dataLearning algorithmsNeural networkRandom forestNeural network modelNeuroendocrine neoplasmsAUC-ROCMachine learning modelsNeuroendocrine markersDiagnostic workupLearning modelsMachine learning modeling algorithmsNetwork modelDiagnosis of neuroendocrine neoplasmsModeling algorithmAlgorithmArea under the curveMachineArea under the curve of receiver operating characteristic curvesReceiver operating characteristic curveNetworkNEC casesCytology casesNon-NENsNatriuretic response prediction equation for use with oral diuretics in heart failure
Ivey-Miranda J, Rao V, Cox Z, Moreno-Villagomez J, Mastache D, Collins S, Testani J. Natriuretic response prediction equation for use with oral diuretics in heart failure. European Heart Journal 2025, 46: 2410-2418. PMID: 40272149, PMCID: PMC12208776, DOI: 10.1093/eurheartj/ehaf268.Peer-Reviewed Original ResearchConceptsMechanisms of diuretic resistanceArea under the curvePoor diuretic responseDiuretic responseHeart failureDiuretic doseOral diureticsNatriuretic responseHF patient cohortsLoop diuretic doseOral loop diureticsUrine samplesTimed urine collectionsOral loopDiuretic resistanceLoop diureticsDiuretic administrationUrine volumePatient cohortUrine collectionStudy visitsDiureticsPatientsUrineDoseThe Disposition Index in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes
Ismail H, Cuthbertson D, Galderisi A, Libman I, Jacobsen L, Moran A, Petrelli A, Atkinson M, Redondo M, Hannon T, Mather K, Sosenko J. The Disposition Index in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes. Diabetes 2025, 74: 1196-1204. PMID: 40173211, PMCID: PMC12185960, DOI: 10.2337/db24-1000.Peer-Reviewed Original ResearchConceptsFirst-phase insulin responseArea under the curveArea under the curve ratioType 1 diabetesB cell functionAutoantibody-positive individualsDPT-1Glucose tolerance testMatsuda indexDisposition indexRegression modelsDiabetic rangeAnalyzed cross-sectionallyTolerance testDiabetes Prevention Trial-Type 1Oral glucose tolerance testProgression to type 1 diabetesStudy participantsCox regression modelsAntibody-positive relativesInsulin secretionPrediction of T1DRisk scoreIntravenous glucose tolerance testMeasure of B-cell functionEvaluating observer reliability and diagnostic accuracy of CT-LEFAT criteria for post-treatment head and neck lymphedema: A prospective blinded comparative analysis
West N, Attia S, Kaffey Z, Dede C, Mulder S, El-Habashy D, Neuberger R, Naser M, Frank S, Mao S, McMillan H, Smith B, Rosenthal D, Lai S, Hutcheson K, Moreno A, Fuller C, Group A. Evaluating observer reliability and diagnostic accuracy of CT-LEFAT criteria for post-treatment head and neck lymphedema: A prospective blinded comparative analysis. Oral Oncology 2025, 164: 107265. PMID: 40174310, PMCID: PMC12087970, DOI: 10.1016/j.oraloncology.2025.107265.Peer-Reviewed Original ResearchConceptsHead and neck cancerArea under the curveDiagnostic accuracyRadiation therapyFat strandingHead-and-neck cancer patients treated with RTPatients treated with RTContrast-enhanced CT scanHead and neck lymphedemaIntra-observer agreementEvaluate diagnostic accuracyROC-AUC analysisNeck lymphedemaNeck cancerInter-observer reliabilityIntra-rater reliabilityCT scanFleiss’ kappa analysisDiagnostic performanceInter-rater reliabilityIntra-observerAUC analysisKappa analysisLymphedemaPhysician ratersPrediction of Hepatitis C Virus Perinatal Transmission in Pregnant Individuals With Hepatitis C Virus Infection
Sandoval G, Saade G, Hughes B, Clifton R, Reddy U, Bartholomew A, Salazar A, Chien E, Tita A, Thorp J, Metz T, Wapner R, Sabharwal V, Simhan H, Swamy G, Heyborne K, Sibai B, Grobman W, El-Sayed Y, Casey B, Parry S, Macones G, Prasad M. Prediction of Hepatitis C Virus Perinatal Transmission in Pregnant Individuals With Hepatitis C Virus Infection. Obstetrics And Gynecology 2025, 145: 449-452. PMID: 40014859, PMCID: PMC11925659, DOI: 10.1097/aog.0000000000005872.Peer-Reviewed Original ResearchConceptsHepatitis C virus infectionPerinatal transmissionHepatitis C virusHepatitis C virus perinatal transmissionPregnant individualsEunice Kennedy Shriver National Institute of Child HealthTransmission of HCV infectionPerinatal transmission rateHCV RNA titersNeonatal follow-upC virus infectionPositive HCV antibodyMulticenter observational studyArea under the curveNational Institute of Child HealthInstitute of Child HealthAntibody-positive participantsAntepartum bleedingHCV infectionHCV antibodiesFollow-upRNA titersC virusObservational studyClinical counselingMachine learning and computational fluid dynamics derived FFRCT demonstrate comparable diagnostic performance in patients with coronary artery disease; A Systematic Review and Meta-Analysis
Narimani-Javid R, Moradi M, Mahalleh M, Najafi-Vosough R, Arzhangzadeh A, Khalique O, Mojibian H, Kuno T, Mohsen A, Alam M, Shafiei S, Khansari N, Shaghaghi Z, Nozhat S, Hosseini K, Hosseini S. Machine learning and computational fluid dynamics derived FFRCT demonstrate comparable diagnostic performance in patients with coronary artery disease; A Systematic Review and Meta-Analysis. Journal Of Cardiovascular Computed Tomography 2025, 19: 232-246. PMID: 39988511, DOI: 10.1016/j.jcct.2025.02.004.Peer-Reviewed Original ResearchArea under the curveDiagnostic odds ratioDiagnostic performanceComputed tomography-derived fractional flow reserveDiagnostic performance of FFRCTHemodynamically significant coronary artery stenosisSignificant coronary artery stenosisMeta-analysisPer-patient levelReceiver operating characteristic curveCoronary artery diseaseCoronary artery stenosisPer-vessel levelFractional flow reserveNoninvasive diagnostic techniquesMachine learningInvasive FFRPooled specificityArtery diseaseArtery stenosisFlow reserveOdds ratioCochrane LibraryFFRCTPatientsThe role of right ventricular systolic pressure and ARISCAT score in perioperative pulmonary risk assessment
Tatsuoka Y, He Z, Lin H, Notarianni A, Carr Z. The role of right ventricular systolic pressure and ARISCAT score in perioperative pulmonary risk assessment. Brazilian Journal Of Anesthesiology 2025, 75: 844597. PMID: 39971234, PMCID: PMC11914786, DOI: 10.1016/j.bjane.2025.844597.Peer-Reviewed Original ResearchConceptsRight ventricular systolic pressurePostoperative pulmonary complicationsArea under the curveARISCAT scoreVentricular systolic pressureReceiver operating characteristic curvePulmonary hypertensionRespiratory failureHigh-risk populationPrimary endpointRisk stratificationSurgical proceduresSystolic pressurePostoperative pulmonary complications incidenceSource of increased morbidityAssess Respiratory RiskDiagnosis of PHPreoperative risk assessmentAdjusted multivariable logistic regression modelsMultivariate logistic regression modelComposite of pneumoniaPulmonary complicationsPreoperative investigationsSecondary endpointsPulmonary aspirationOral microbiota among treatment-naïve adolescents with depression: A case-control study
Zeng Y, Jia X, Li H, Zhou N, Liang X, Liu K, Yang B, Xiang B. Oral microbiota among treatment-naïve adolescents with depression: A case-control study. Journal Of Affective Disorders 2025, 375: 93-102. PMID: 39855566, PMCID: PMC11934967, DOI: 10.1016/j.jad.2025.01.089.Peer-Reviewed Original ResearchMajor depressive disorderArea under the curveCognitive functionOral microbiotaCase-control studyReceiver operating characteristicAdolescent depressionDSM-5 major depressive disorderAssociated with major depressive disorderTreatment naive individualsNon-depressed individualsMorning saliva samplesHealthy control groupGroup of adolescentsDepressive disorderDSM-5Visual breadthDelayed memoryDepression groupOral healthOral bacteriaHC individualsGut microbiota changesHC groupOral microbesA Glucose Fraction Independent of Insulin Secretion: Implications for Type 1 Diabetes Progression in Autoantibody-Positive Cohorts
Sosenko J, Cuthbertson D, Jacobsen L, Redondo M, Sims E, Ismail H, Herold K, Skyler J, Nathan B, Groups D. A Glucose Fraction Independent of Insulin Secretion: Implications for Type 1 Diabetes Progression in Autoantibody-Positive Cohorts. Diabetes Technology & Therapeutics 2025, 27: 179-186. PMID: 39757867, PMCID: PMC12084817, DOI: 10.1089/dia.2024.0422.Peer-Reviewed Original ResearchConceptsIndependent of insulin secretionArea under the curveAUC C-peptideAutoantibody-positive individualsC-peptideInsulin secretionAUC glucoseGlucose toleranceFirst-phase insulin responseDiabetes Prevention Trial-Type 1Type 1 diabetes progressionOral glucose tolerance test dataGlucose tolerance test dataPrediction of T1DImpaired glucose toleranceOral glucose toleranceType 1 diabetesDPT-1TrialNet PathwayIncreased glycemiaInsulin responseInverse correlationSecretionT1DLack of correlation
2024
Development and validation of the BRief Eating Disorder Screener (BREDS) for US veterans in healthcare and community settings
Masheb R, Batten A, Siegel S, Huggins J, Marsh A, Snow J, Munro L, Vogt D, White M, Maguen S. Development and validation of the BRief Eating Disorder Screener (BREDS) for US veterans in healthcare and community settings. General Hospital Psychiatry 2024, 93: 1-8. PMID: 39754995, DOI: 10.1016/j.genhosppsych.2024.12.021.Peer-Reviewed Original ResearchConceptsEating disorder diagnosisDSM-5Disorder diagnosisDSM-5 eating disorder diagnosesPrediction of diagnosisDiagnostic InterviewVA healthcareCommunity settingsUS veteransScreenerNational surveyArea under the curveItemsVeteransHealthcareYour bodyBriefSurveyYour lifeScreeningDiagnosisValidityInterviewsMulticenter validation of automated detection of paramagnetic rim lesions on brain MRI in multiple sclerosis
Chen L, Ren Z, Clark K, Lou C, Liu F, Cao Q, Manning A, Martin M, Luskin E, O'Donnell C, Azevedo C, Calabresi P, Freeman L, Henry R, Longbrake E, Oh J, Papinutto N, Bilello M, Song J, Kaisey M, Sicotte N, Reich D, Solomon A, Ontaneda D, Sati P, Absinta M, Schindler M, Shinohara R, Cooperative T. Multicenter validation of automated detection of paramagnetic rim lesions on brain MRI in multiple sclerosis. Journal Of Neuroimaging 2024, 34: 750-757. PMID: 39410780, DOI: 10.1111/jon.13242.Peer-Reviewed Original ResearchParamagnetic rim lesionsArea under the curveRim lesionsMultiple sclerosisPrognosis of MSBiomarkers of chronic inflammationWhite matter lesionsMulticenter settingMulticenter studyMulticenter validationChronic inflammationBrain MRIClinical trialsIdentified lesionsMulticenterMS diagnosisLesionsParamagnetic rimAutomated segmentation methodMRIMRI biomarkersMulticenter datasetDiagnosisSclerosisTeam of trained raters12444 Steroid Profiling And Circadian Cortisol Secretion In Patients With Mild Autonomous Cortisol Secretion: A Single-Center Cross-Sectional Study
Saini J, Singh S, Ebbehøj A, Zhang C, Nathani R, Fell V, Atkinson E, Achenbach S, Rivard A, Singh R, Grebe S, Bancos I. 12444 Steroid Profiling And Circadian Cortisol Secretion In Patients With Mild Autonomous Cortisol Secretion: A Single-Center Cross-Sectional Study. Journal Of The Endocrine Society 2024, 8: bvae163.295. PMCID: PMC11454430, DOI: 10.1210/jendso/bvae163.295.Peer-Reviewed Original ResearchUrine steroid metabolomeAutonomous cortisol secretionSteroid metabolomeReference subjectsCortisol secretionMild autonomous cortisol secretionSteroid profileSteroid productionSingle-center cross-sectional studyCompared to reference subjectsUrine steroid profileSubgroup of patientsArea under the curveHigh-resolution mass spectrometry assayCross-sectional studyCircadian cortisol secretionMass spectrometry assaySingle-centerAndrogen ratioFree cortisolCircadian secretionPatientsMetabolomicsSteroidsSeparate days
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