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Literature-related discovery and innovation: Chronic kidney disease

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  • Kostoff, Ronald N.
  • Patel, Uptal

Abstract

Different approaches for preventing, reducing, halting, and reversing chronic kidney disease (CKD) have been described in the medical literature. However, all related factors have not been identified together. To overcome these limitations, we used an LRDI-based methodology (potentially applicable to any disease) based on the following holistic principle: a necessary, but not sufficient, condition for restorative treatment effectiveness is that potential causes must be removed initially or in parallel with treatment. Literature-Related Discovery and Innovation (LRDI) is a text mining approach that integrates discovery generation from disparate literatures with the wealth of knowledge contained in prior scientific publications. To support the central requirement of the holistic principle above, LRDI seeks to identify foundational causes that, if eliminated, could potentially reverse chronic and infectious diseases.

Suggested Citation

  • Kostoff, Ronald N. & Patel, Uptal, 2015. "Literature-related discovery and innovation: Chronic kidney disease," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 341-351.
    • Handle: RePEc:eee:tefoso:v:91:y:2015:i:c:p:341-351
    DOI: 10.1016/j.techfore.2014.09.013
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    References listed on IDEAS

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    1. Neil R. Smalheiser, 2012. "Literature-based discovery: Beyond the ABCs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 218-224, February.
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    Cited by:

    1. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    2. Zhang, Yi & Robinson, Douglas K.R. & Porter, Alan L. & Zhu, Donghua & Zhang, Guangquan & Lu, Jie, 2016. "Technology roadmapping for competitive technical intelligence," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 175-186.

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