Methods used in the development of common data models for health data: Scoping review. JMIR Med. Inform., (11):e45116, August 2023. [PUMA: Observational Data Healthcare; Interoperability; health Repositories; Interoperability Partnership elements; elements Healthcare model; ; Process; Medical Informatics; data; harmonisation; Suggestive data Process record; stakeholder Standardized Repositories Outcomes Partnership; involvement common record Development harmonisation model Informatics electronic]
Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)Januar 2024. [PUMA: problems; visualization learning; data machine analysis; AutoML; classification]
Multi-source dataset of e-commerce products with attributes for property matching. Data Brief, (41)107884:107884, Elsevier BV, April 2022. [PUMA: integration; engineering; Data Ontology; Property matching]
Toward Veracity Assessment in RDF Knowledge Bases: An Exploratory Analysis. J. Data and Information Quality, (9)3Association for Computing Machinery, New York, NY, USA, Februar 2018. [PUMA: exploratory trustworthiness, benchmark, fact DeFacto, data checking, quality, analysis data, linked] URL
Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology. BMC Med. Inform. Decis. Mak., (20)1:28, Februar 2020. [PUMA: decision-making; workflow; Haematology; Support Mathematical therapy Clinical Data Routine treatment management; simulation; modelling; system optimization; Individual Computer planning; Model-based]
Automated algorithm selection: Survey and perspectives. Evol. Comput., (27)1:3--45, MIT Press, 2019. [PUMA: feature-based learning; metalearning data analysis; optimisation; automated streams.; exploratory combinatorial continuous machine approaches; Automated selection; algorithm configuration; landscape]
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: a disease; HCC, or intelligence; liver multivariable non-alcoholic multimodal ML, artificial WSIs, images; prediction support integration TACE, DICOM, AI, network; deep neural Digital Diagnosis; MVI, transarterial fatty microvascular convolutional in learning; imaging; Communications invasion; NAFLD, chemoembolisation; hepatocellular Reporting steatohepatitis; Transparent Individual slide machine Prognosis Artificial data for NASH, whole Medicine; TRIPOD, of CNN, and Imaging carcinoma; diagnostic system; model]
ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern Recognition, (147):110138, 2024. [PUMA: Tabular Convex Imbalanced learning, GAN, data LoRAS, space data,] URL
A standardized clinical data harmonization pipeline for scalable AI application deployment (FHIR-DHP): Validation and usability study. JMIR Med. Inform., (11):e43847, JMIR Publications Inc., März 2023. [PUMA: intelligence; mart AI care; deployment; IV; artificial fast application; information resources; care data; medical cooperation; data standardization for healthcare interoperability; AI; unit; FHIR; usability MIMIC diagnosis; interoperability patient pipeline; research; intensive]
Ten topics to get started in medical informatics research. J. Med. Internet Res., (25):e45948, Juli 2023. [PUMA: clinical medical health; informatics; data communication; health digital data; interdisciplinary research]