2025
Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records
Liu X, Gong W, Chen X, Li Z, Liu Y, Wang L, Liu Q, Sun X, Liu X, Chen X, Shi Y, Yu H. Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records. Pattern Recognition 2025, 165: 111646. DOI: 10.1016/j.patcog.2025.111646.BooksLabeled dataGeneralization performanceExpert annotationsArtificial intelligencePre-training datasetSuperior generalization performanceState-of-the-artMedical artificial intelligencePerformance of AI modelsNasal endoscopic imagesLearning frameworkAI modelsMultiple imagesSemantic representationDiagnostic tasksFine-tuningTask-specificUniversal representationDatasetExperimental resultsDisease classificationEndoscopic imagesDiagnosis of diseasesAnnotationFoundation modelAutomated transformation of unstructured cardiovascular diagnostic reports into structured datasets using sequentially deployed large language models
Vasisht Shankar S, Dhingra L, Aminorroaya A, Adejumo P, Nadkarni G, Xu H, Brandt C, Oikonomou E, Pedroso A, Khera R. Automated transformation of unstructured cardiovascular diagnostic reports into structured datasets using sequentially deployed large language models. European Heart Journal - Digital Health 2025, ztaf030. DOI: 10.1093/ehjdh/ztaf030.Peer-Reviewed Original ResearchA foundation model for generalizable cancer diagnosis and survival prediction from histopathological images
Yang Z, Wei T, Liang Y, Yuan X, Gao R, Xia Y, Zhou J, Zhang Y, Yu Z. A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images. Nature Communications 2025, 16: 2366. PMID: 40064883, PMCID: PMC11894166, DOI: 10.1038/s41467-025-57587-y.Peer-Reviewed Original ResearchConceptsWhole slide imagesLeveraging self-supervised learningScarcity of annotated dataHistopathological imagesSelf-supervised learningPre-training approachSelf-supervised modelPre-trained modelsApplication of artificial intelligenceSmall-scale dataIntelligent healthcareEnhance model performanceExpert annotationsPre-trainingArtificial intelligenceComputational pathologyImaging modelEfficient solutionSlide imagesCancer classificationModel performanceRepresentationImagesCancer diagnosisIntelligence
2024
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation
Liu C, Amodio M, Shen L, Gao F, Avesta A, Aneja S, Wang J, Del Priore L, Krishnaswamy S. CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation. Lecture Notes In Computer Science 2024, 15008: 155-165. DOI: 10.1007/978-3-031-72111-3_15.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationLack of labeled dataUnsupervised deep learning frameworkSegmenting medical imagesDeep learning frameworkBrain MRI imagesRetinal fundus imagesContrastive learningLearning frameworkUnsupervised methodDeep learningExpert annotationsData topologyMedical imagesGranularity levelsEmbedding mapHausdorff distanceFundus imagesDice coefficientImage dataEmbeddingAnnotationLearningMRI imagesA Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation
Wen A, Wang L, He H, Fu S, Liu S, Hanauer D, Harris D, Kavuluru R, Zhang R, Natarajan K, Pavinkurve N, Hajagos J, Rajupet S, Lingam V, Saltz M, Elowsky C, Moffitt R, Koraishy F, Palchuk M, Donovan J, Lingrey L, Stone-DerHagopian G, Miller R, Williams A, Leese P, Kovach P, Pfaff E, Zemmel M, Pates R, Guthe N, Haendel M, Chute C, Liu H, Collaborative C, Initiative T. A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation. JMIR Medical Informatics 2024, 12: e49997. PMID: 39250782, PMCID: PMC11420592, DOI: 10.2196/49997.Peer-Reviewed Original ResearchNatural language processingNatural language processing algorithmsNatural language processing toolkitNatural language processing systemsProcessing toolkitNatural language processing tasksUnified Medical Language SystemClinical natural language processingAlgorithm developmentMedical Language SystemLanguage processing systemDevelopment approachNLP tasksTime-critical natureHuman expertsNatural language processing resultsExpert annotationsLanguage processingTraining setClinical narrativesNatural language processing extractsTest setAlgorithmPostacute sequelae of SARS-CoV-2 infectionProcessing system
2023
The Yale Glioma Dataset: Developing An Open Access, Annotated MRI Database
Sala M, Lost J, Tillmanns N, Merkaj S, von Reppert M, Ramakrishnan D, Bousabarah K, Huttner A, Aneja S, Avesta A, Omuro A, Aboian M. The Yale Glioma Dataset: Developing An Open Access, Annotated MRI Database. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2023 DOI: 10.58530/2023/4511.Peer-Reviewed Original Research
2016
Weakly supervised learning of biomedical information extraction from curated data
Jain S, R. K, Kuo T, Bhargava S, Lin G, Hsu C. Weakly supervised learning of biomedical information extraction from curated data. BMC Bioinformatics 2016, 17: s1. PMID: 26817711, PMCID: PMC4847485, DOI: 10.1186/s12859-015-0844-1.Peer-Reviewed Original ResearchConceptsTraining examplesInformation extractionGenome-wide association studiesCommittee of weak classifiersCurated dataInformation extraction tasksBiomedical information extractionWeakly supervised learningCost-sensitive learningBiomedical text miningSupervised machine learningNoisy labelsWeak classifiersExtraction taskInformation extractorExpert annotationsBig dataMachine learningText miningBaseline counterpartExperimental resultsAssociation studiesTarget phenotypeBiomedical databasesTask
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