Chapter 13
Smart Learning Using Big and Small
Data for Mobile and IOT e-Health
Pei-Yun Sabrina Hsueh, Xinyu Hu, Ying Kuen Cheung, Dominik Wolff,
Michael Marschollek, and Jeff Rogers
There are no secrets to success. It is the result of preparation,
hard work, and learning from failure.
Colin Powell
Contents
13.1 Introduction .............................................................................. 608
13.1.1 Key Challenges in Smart Learning for Mobile and IOT e-Health.......... 609
13.1.2 Incorporating Domain Knowledge in Data-Driven Learning............... 611
13.1.3 Structure of the Book Chapter ............................................... 611
13.2 Predictive and Reinforcement Learning for Life Coaching ........................... 612
13.2.1 Background: Stress-Activity Data ........................................... 612
13.2.2 Case Study: N-of-1 Analytical Methods .................................... 613
13.2.3 Case Study: Actionable Learning Methods ................................. 615
13.3 Knowledge Symbiosis Learning for Care Management ............................... 618
13.3.1 Application: AI in Intelligent Education for Healthcare .................... 618
13.3.2 Background in Intelligent Tutoring Systems ................................ 619
13.3.3 Challenges Facing the Development of ITS ................................. 621
13.3.4 Case Study: Implicit Knowledge Learning for Nurses ..................... 622
13.3.5 Case Study: Implicit Knowledge Learning for Caregivers ................. 623
13.4 Continuous Learning for In-Field Decision-Making .................................. 627
13.4.1 Application: Risk Inference for Traumatic Brain Injury .................... 627
13.5 Discussion ............................................................................... 629
References ........................................................................................ 631
P.-Y. S. Hsueh ()
Viome, Inc., Yorktown Heights, NY, USA
X. Hu · Y. K. Cheung
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York,
NY, USA
D. Wolff · M. Marschollek
Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical
School, Hanover, Germany
J. Rogers
IBM Watson Research Center, Yorktown Heights, NY, USA
© Springer Nature Switzerland AG 2020
F. Firouzi et al. (eds.), Intelligent Internet of Things,
https://doi.org/10.1007/978-3-030-30367-9_13
607
Smart Learning Using Big and Small
Data for Mobile and IOT e-Health
Pei-Yun Sabrina Hsueh, Xinyu Hu, Ying Kuen Cheung, Dominik Wolff,
Michael Marschollek, and Jeff Rogers
There are no secrets to success. It is the result of preparation,
hard work, and learning from failure.
Colin Powell
Contents
13.1 Introduction .............................................................................. 608
13.1.1 Key Challenges in Smart Learning for Mobile and IOT e-Health.......... 609
13.1.2 Incorporating Domain Knowledge in Data-Driven Learning............... 611
13.1.3 Structure of the Book Chapter ............................................... 611
13.2 Predictive and Reinforcement Learning for Life Coaching ........................... 612
13.2.1 Background: Stress-Activity Data ........................................... 612
13.2.2 Case Study: N-of-1 Analytical Methods .................................... 613
13.2.3 Case Study: Actionable Learning Methods ................................. 615
13.3 Knowledge Symbiosis Learning for Care Management ............................... 618
13.3.1 Application: AI in Intelligent Education for Healthcare .................... 618
13.3.2 Background in Intelligent Tutoring Systems ................................ 619
13.3.3 Challenges Facing the Development of ITS ................................. 621
13.3.4 Case Study: Implicit Knowledge Learning for Nurses ..................... 622
13.3.5 Case Study: Implicit Knowledge Learning for Caregivers ................. 623
13.4 Continuous Learning for In-Field Decision-Making .................................. 627
13.4.1 Application: Risk Inference for Traumatic Brain Injury .................... 627
13.5 Discussion ............................................................................... 629
References ........................................................................................ 631
P.-Y. S. Hsueh ()
Viome, Inc., Yorktown Heights, NY, USA
X. Hu · Y. K. Cheung
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York,
NY, USA
D. Wolff · M. Marschollek
Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical
School, Hanover, Germany
J. Rogers
IBM Watson Research Center, Yorktown Heights, NY, USA
© Springer Nature Switzerland AG 2020
F. Firouzi et al. (eds.), Intelligent Internet of Things,
https://doi.org/10.1007/978-3-030-30367-9_13
607