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Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs

  • Thomas Marshall
  • Tiffiany Champagne-Langabeer
  • Darla Castelli
  • Deanna Hoelscher
Review
Part of the following topical collections:
  1. Special Issue on Artificial Intelligence in Health and Medicine

Abstract

Objective

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies.

Methods

The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience.

Results

The paper provides a forward view of the impact of artificial intelligence on our human–computer support and research methods in health and life science research.

Conclusions

By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Keywords

Cognitive computing Artificial intelligence Obesity intervention 

Notes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Auburn UniversityAuburnUSA
  2. 2.School of Biomedical InformaticsHoustonUSA
  3. 3.University of TexasAustinUSA
  4. 4.The University of Texas Health Science Center at Houston, School of Public HealthAustinUSA

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