Cargando…

Big Data in Laboratory Medicine—FAIR Quality for AI?

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day—from simple numerical results from, e.g., sodium measurements to highly complex output of “-omics” analyses, as well as quality control results and metadata. Processing, connecting, storing, and orderin...

Descripción completa

Detalles Bibliográficos
Autores principales:	Blatter, Tobias Ueli, Witte, Harald, Nakas, Christos Theodoros, Leichtle, Alexander Benedikt
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9406962/ https://www.ncbi.nlm.nih.gov/pubmed/36010273 http://dx.doi.org/10.3390/diagnostics12081923

Ejemplares similares

The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application
por: Blatter, Tobias Ueli, et al.
Publicado: (2023)

Machine Learning Prediction of Hypoglycemia and Hyperglycemia From Electronic Health Records: Algorithm Development and Validation
por: Witte, Harald, et al.
Publicado: (2022)

AI Fairness
por: Mahoney, Trisha
Publicado: (2020)

Differential Fairness: An Intersectional Framework for Fair AI †
por: Islam, Rashidul, et al.
Publicado: (2023)

Explainable AI as evidence of fair decisions
por: Leben, Derek
Publicado: (2023)

Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling
por: Nakas, Christos T., et al.
Publicado: (2016)

AI, big data, and the future of consent
por: Andreotta, Adam J., et al.
Publicado: (2021)

Computational Evidence for Laboratory Diagnostic Pathways: Extracting Predictive Analytes for Myocardial Ischemia from Routine Hospital Data
por: Liniger, Zara, et al.
Publicado: (2022)

Laboratory Data Quality Evaluation in the Big Data Era
por: Kim, Sollip
Publicado: (2023)

AI, big data, and robots for the evolution of biotechnology
por: Kim, Haseong
Publicado: (2019)

FAIRly big: A framework for computationally reproducible processing of large-scale data
por: Wagner, Adina S., et al.
Publicado: (2022)

Big Data, artificial intelligence and laboratory medicine: time for integration
por: Gruson, Damien
Publicado: (2021)

A translational perspective towards clinical AI fairness
por: Liu, Mingxuan, et al.
Publicado: (2023)

FAIR for AI: An interdisciplinary and international community building perspective
por: Huerta, E. A., et al.
Publicado: (2023)

Reproducible big data science: A case study in continuous FAIRness
por: Madduri, Ravi, et al.
Publicado: (2019)

FACT and FAIR with Big Data allows objectivity in science: The view of crystallography
por: Helliwell, John R.
Publicado: (2019)

Detecting shortcut learning for fair medical AI using shortcut testing
por: Brown, Alexander, et al.
Publicado: (2023)

Correction: Reproducible big data science: A case study in continuous FAIRness
por: Madduri, Ravi, et al.
Publicado: (2023)

A FAIR and AI-ready Higgs boson decay dataset
por: Chen, Yifan, et al.
Publicado: (2022)

Fairness and accountability of AI in disaster risk management: Opportunities and challenges
por: Gevaert, Caroline M., et al.
Publicado: (2021)

Generating FAIR research data in experimental tribology
por: Garabedian, Nikolay T., et al.
Publicado: (2022)

You Can’t Have AI Both Ways: Balancing Health Data Privacy and Access Fairly
por: Bak, Marieke, et al.
Publicado: (2022)

Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital
por: Musy, Sarah N, et al.
Publicado: (2020)

Artificial intelligence (AI) and big data in cancer and precision oncology
por: Dlamini, Zodwa, et al.
Publicado: (2020)

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome
por: Lesche, Dorothea, et al.
Publicado: (2016)

SQL Server Big Data Clusters: Data Virtualization, Data Lake, and AI Platform
por: Weissman, Benjamin
Publicado: (2020)

Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
por: Panesar, Arjun
Publicado: (2020)

Machine learning and AI for healthcare: big data for improved health outcomes
por: Panesar, Arjun
Publicado: (2019)

DAOS: Nextgen Storage Stack for AI, Big Data and Exascale HPC
por: Lombardi, Johann
Publicado: (2021)

Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery
por: Tripathi, Manish Kumar, et al.
Publicado: (2021)

Editorial: Heterogeneous Computing for AI and Big Data in High Energy Physics
por: D’Agostino, Daniele, et al.
Publicado: (2021)

The adaptive immune receptor repertoire community as a model for FAIR stewardship of big immunology data
por: Scott, Jamie K., et al.
Publicado: (2020)

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma
por: Leichtle, Alexander Benedikt, et al.
Publicado: (2012)

Big data demystified: how to use big data, data science and AI to make better business decisions and gain competitive advantage
por: Stephenson, David
Publicado: (2018)

An introduction to data: everything you need to know about AI, big data and data science
por: Corea, Francesco
Publicado: (2018)

Algorithmic fairness in computational medicine
por: Xu, Jie, et al.
Publicado: (2022)

Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study
por: Herzig, David, et al.
Publicado: (2020)

New AI laboratory for the NHS
por: Steventon, Adam, et al.
Publicado: (2019)

Editorial on Machine Learning, AI and Big Data Methods and Findings for COVID-19
por: Chang, Victor, et al.
Publicado: (2021)

ERP Staff versus AI recruitment with employment real-time big data
por: Strang, Kenneth David, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_mod7925i4s7rj06tpiikullboh