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Data-driven Clinical Decision Processes

Section edited by Enrico Capobianco

Changes and transformations enabled by Big Data have direct effects on Translational Medicine.
At one end, superior precision is expected from a more data-intensive and individualized medicine, thus accelerating scientific discovery and innovation (in diagnosis, therapy, disease management etc.).
At the other end, the scientific method needs to adapt to the increased diversity that data presents, and this too can be a beneficial aspect, potentially revealing more on how a disease manifests or progresses.

Patient-focused health data provides augmented complexity too, far beyond the simple need of testing hypotheses or validating models. Clinical decision support systems (CDSS) will increasingly deal with such complexity by developing efficient high-performance algorithms and creating a next generation inferential tools for clinical use. Additionally, new protocols for sharing digital information and effectively integrating patients data will need to be CDSS embedded features in view of suitable data harmonization aimed at improved diagnosis, therapy assessment and prevention.

  1. Content type: Research

    Chronic kidney disease (CKD) leads to end-stage renal failure and cardiovascular events. An attribute to these progressions is abnormalities in inflammation, which can be evaluated using the neutrophil-to-lymp...

    Authors: Qiongjing Yuan, Jinwei Wang, Zhangzhe Peng, Qiaoling Zhou, Xiangcheng Xiao, Yanyun Xie, Wei Wang, Ling Huang, Wenbin Tang, Danni Sun, Luxia Zhang, Fang Wang, Ming-Hui Zhao, Lijian Tao, Kevin He and Hui Xu

    Citation: Journal of Translational Medicine 2019 17:86

    Published on:

  2. Content type: Editorial

    Changes and transformations enabled by Big Data have direct effects on Translational Medicine. At one end, superior precision is expected from a more data-intensive and individualized medicine, thus accelerati...

    Authors: Enrico Capobianco

    Citation: Journal of Translational Medicine 2019 17:44

    Published on:

  3. Content type: Research

    Sequence information generated from next generation sequencing is often computationally phased using haplotype-phasing algorithms. Utilizing experimentally derived allele or haplotype information improves this...

    Authors: Kshitij Srivastava, Kurt R. Wollenberg and Willy A. Flegel

    Citation: Journal of Translational Medicine 2019 17:43

    Published on:

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