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521
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522por Pivarski, Jim, Rodrigues, Eduardo, Pedro, Kevin, Shadura, Oksana, Krikler, Benjamin, Stewart, Graeme A.“…It describes the adoption of Python and data science tools in HEP, discusses the likelihood of future scenarios, and recommendations for action by the HEP community.…”
Publicado 2022
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523
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524Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework“…In addition, this review discusses the utility of data science tools as a means of identifying novel, modifiable risk factors for suicide, and triangulation as an overarching approach to ensuring rigor in suicide research as means of addressing existing knowledge gaps and strengthening future research.…”
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525
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526por Mariano, Diego, Da Fonseca Júnior, Neli José, Santos, Lucianna Helene, de Melo-Minardi, Raquel CardosoEnlace del recurso
Publicado 2023
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527por Seth, Puneet, Hueppchen, Nancy, Miller, Steven D, Rudzicz, Frank, Ding, Jerry, Parakh, Kapil, Record, Janet D“…The increasingly sophisticated and rapidly evolving application of artificial intelligence in medicine is transforming how health care is delivered, highlighting a need for current and future physicians to develop basic competency in the data science that underlies this topic. Medical educators must consider how to incorporate central concepts in data science into their core curricula to train physicians of the future. …”
Publicado 2023
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528“…Therefore, we propose an integrated data science framework to inform efficient and sustainable RRCC from organic waste based on the review. …”
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529por Cordeiro, João Rala, Mosca, Sara, Correia-Costa, Ana, Ferreira, Cátia, Pimenta, Joana, Correia-Costa, Liane, Barros, Henrique, Postolache, Octavian“…The present research based on data from children that have been followed since birth in a previously established cohort study (Generation XXI, Porto, Portugal), taking advantage of State-of-the-Art (SoA) data science techniques and methods, including Neural Architecture Search (NAS), explainable Artificial Intelligence (XAI), and Deep Learning (DL), aimed to explore the hidden value of data, namely on electrocardiogram (ECG) records performed during follow-up visits. …”
Publicado 2023
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530
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531
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532
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533“…We focus heavily on how to apply and evaluate the data science methods, and resulting strategies, in a real-world business setting. …”
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534por Banda, Juan M.“…The Observational Health Data Science and Informatics (OHDSI) initiative combines over 100 controlled vocabularies into its own. …”
Publicado 2019
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536por Kashyap, Mehr, Seneviratne, Martin, Banda, Juan M, Falconer, Thomas, Ryu, Borim, Yoo, Sooyoung, Hripcsak, George, Shah, Nigam H“…We developed 10 phenotype classifiers using this approach and evaluated performance across multiple sites within the Observational Health Data Sciences and Informatics (OHDSI) network. MATERIALS AND METHODS: We constructed classifiers using the Automated PHenotype Routine for Observational Definition, Identification, Training and Evaluation (APHRODITE) R-package, an open-source framework for learning phenotype classifiers using datasets in the Observational Medical Outcomes Partnership Common Data Model. …”
Publicado 2020
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537“…Conclusions : The ever-increasing amount of data available offers endless opportunities to develop methods and tools that could assist public health surveillance and intervention belonging to the growing field of public health Data Science. The transition from proofs of concept to real world applications and adoption by health authorities remains a difficult leap to make.…”
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538Wheels of All Colors, Shapes, and Sizes Working Together: A Vision of Common Purpose in Data Sciencepor Callaghan, SarahEnlace del recurso
Publicado 2020
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539por Hollaway, Michael J., Dean, Graham, Blair, Gordon S., Brown, Mike, Henrys, Peter A., Watkins, John“…We set out a clear and defined research roadmap to serve as a focal point for an international research community progressing toward a more data-driven and transparent approach to environmental data science, centered on data science labs. This includes ongoing case studies of good practice, with the infrastructural and methodological developments required to enable data science labs to support significant increase in our cross- and trans-disciplinary science capabilities.…”
Publicado 2020
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