Exploring Intelligent Healthcare with Quantum Computing

Classical computers, which include smartphones and laptops, encode information in binary "bits" that can either be 0s or 1s. In a quantum computer, the basic unit of memory is a quantum bit or qubit. Qubits are made using physical systems, such as the spin of an electron or the orientation of a photon. In situations where there are a large number of possible feature combinations, quantum computers can consider them simultaneously. This speeds up the data processing time, thereby allowing doctors to compare much more data in parallel, simultaneously, and all permutations of that data, to discover the best patterns that describe it and thus predict the best treatment options. Quantum computers are faster, but highly sensitive (heat, electromagnetic fields and collisions with air molecules can cause a qubit to lose its quantum properties) and these challenges will also be explored.

The book will explore the field of quantum computing and machine learning for medical data processing.

In healthcare, where there are a large number of possible factors to consider, quantum computers can consider them simultaneously, thereby allowing doctors to compare much, much more data in parallel, simultaneously, and all permutations of that data, to discover the best patterns that describe it, and therefore predict the best treatment options.

In the healthcare industry, quantum computing could accelerate diagnoses, personalizing medicine, and optimizing pricing. Quantum-enhanced machine learning algorithms are particularly relevant to the sector.

Abhishek Kumar is an associate professor in the CSE department at Chandigarh University, Punjab, India, and a post-doctoral fellow at the Ingenium Research Group Lab, Universidad De Castilla-La Mancha, Ciudad Real, Spain. He has more than 13 years of academic teaching experience and over 170 publications in peer-reviewed national and international journals and conferences.

Ashutosh Kumar Dubey is an associate professor in the Department of Computer Science at Chitkara University School of Engineering and Technology, situated in Himachal Pradesh, India. He is a post-doctoral fellow at the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Ciudad Real, Spain. His research interests encompass machine learning, renewable energy, health informatics, nature-inspired algorithms, cloud computing, and big data.

Vincenzo Piuri is a professor of computer engineering at the University of Milan, Italy, an associate professor at the Polytechnic of Milan, Italy and visiting professor at the University of Texas at Austin, USA, and visiting researcher at George Mason University, USA and honorary professor at Obuda University, Hungary; Guangdong University of Petrochemical Technology, China; Northeastern University, China; Muroran Institute of Technology, Japan; Amity University, India; and Galgotias University, India. He is a fellow of the IEEE, a distinguished scientist of ACM, and a senior member of INNS. His research interests include neural networks, biometrics, and image processing.

Joel J.P.C. Rodrigues is with the Amazonas State University, Brazil. He is also the leader of the Center for Intelligence at Fecomércio/CE, Brazil and full professor at Lusófona University, Lisbon, Portugal. Prof. Rodrigues is a Highly Cited Researcher (Clarivate), and leader of NetGNA research group (CNPq). He has authored more than 1250 contributions and he is the EiC of the International Journal of E-Health and Medical Communications.