Healthcare Recommender Systems: Techniques and Recent Developments

The book will explore some promising areas, which include, but are not limited to the following topics:

1. Rudiments of Recommender Systems: Recommender Systems are information filtering systems that uses multiple processes to filter out the results. This book describes the rudiments of recommender systems. Combination units of computation and networking along with other components will be considered.

2. Integration of Technologies in Recommender Systems: This book will demonstrate the relationship between multiple technologies. The changes in the approaches of Healthcare Recommender Systems will be depicted after the emergence of new technologies. Work involved in Pattern Recognition considering such systems can be fast with the use of recent approaches and technologies. Like the way, internet has changed how individuals interact with one another and how recommender systems deal with such situations.

3. Smart Real Time Data Analytics for Recommender Systems: With the rapid growth and recognition of recommender systems in the day-to-day applications, using emerging technologies, data analytics becomes much more convenient. Time data analytics even became more operational when smart devices are used with them, forming smart real time data analytics. Recent Advances in communication systems make it feasible to implement such smart real time data analytics for recommender systems where the data from all connected standpoints can be analysed and managed between the physical locations and computational devices. The volumes of the data collected by these devices are enormously huge and it is reshaping the way businesses are done.

4. Model Based Design Framework of Healthcare Recommender Systems: Framework and design models have traditionally demonstrated the effectiveness of healthcare systems. Architectural design and system models representing how different modules are interconnected with each other, will be part of this book.

5. Control and Optimization of Healthcare Recommender Systems: As smart healthcare systems are evolving, the traditional time driven approaches for control and optimization become inadequate for handling the synchronization of all components of a distributed system. On the contrary, smart healthcare recommender system involves energy-constrained devices and regular communication among constituent devices that can be inefficient. Thus, rather than applying traditional time driven approaches, efficient control and optimization methods for exchanging information amongst nodes need to be devised.

6. Security Aspects and Privacy Issues in Healthcare Recommender Systems: Security and Privacy are major concerns in life critical healthcare recommender systems. Healthcare Recommender Systems deals with life events, which can be critical sometimes. Considering the distinctive characteristics of Healthcare Recommender Systems such as heterogeneity, real‐time availability, resilience to attacks, interoperability, and survivability, security becomes a challenging issue. For instance, privacy concerns are raised due to the integration of components in different technologies that might not have been designed or developed with privacy in mind or due to the increased number of attacks.

7. Existing studies on Explainable AI approaches in Pattern Recognition-based Healthcare Recommender Systems: This book will explain existing approaches towards Artificial Intelligence approaches and will also present studies related to Explainable Artificial Intelligence linked with Pattern Recognition in Healthcare Recommender Systems. The reader can come across the understanding of how explainable AI can be used in Recommender Systems.

8. Applications of Healthcare Recommender Systems: Pattern Recognition in Healthcare Recommender System applications have allowed researchers to collaborate with medical practitioners to comprehend the issues and challenges in a way to deliver solutions that can be tested in practical settings. For instance, the medical equipment’s deployed for the continuous monitoring of the patients and to provide first-aid medicines accordingly, as specified by doctors. Not only this, there are different application scenarios of Recommender Systems in the healthcare domain, such as Food Recommendation, Drug Recommendation, health status prediction, physical activity recommendation, and healthcare professional recommendation. Such scenarios will be discussed with their use case applications also. 

Submission of author details, abstract and outlining of the chapter : May 25, 2023

Full chapter Submission : June 05, 2023

Dr. Simar Preet Singh

Bennett University, Greater Noida, dr.simarpreetsingh@gmail.com

Dr. Deepak Kumar Jain

Chongqing University of Posts and Telecommunications, Chongqing, China, deepak@cqupt.edu.cn

Prof. Johan Debayle

Ecole Nationale Supérieure des Mines de Saint-Etienne (ENSM-SE), France, debayle@emse.fr