Artificial intelligence in healthcare: a mastery

ABSTRACT

There is a vast development of artificial intelligence (AI) in recent years. Computational technology, digitized data collection and enormous advancement in this field have allowed AI applications to penetrate the core human area of specialization. In this review article, we describe current progress achieved in the AI field highlighting constraints on smooth development in the field of medical AI sector, with discussion of its implementation in healthcare from a commercial, regulatory and sociological standpoint. Utilizing sizable multidimensional biological datasets that contain individual heterogeneity in genomes, functionality and milieu, precision medicine strives to create and optimize approaches for diagnosis, treatment methods and assessment. With the arise of complexity and expansion of data in the health-care industry, AI can be applied more frequently. The main application categories include indications for diagnosis and therapy, patient involvement and commitment and administrative tasks. There has recently been a sharp rise in interest in medical AI applications due to developments in AI software and technology, particularly in deep learning algorithms and in artificial neural network (ANN). In this overview, we enlisted the major categories of issues that AI systems are ideally equipped to resolve followed by clinical diagnostic tasks. It also includes a discussion of the future potential of AI, particularly for risk prediction in complex diseases, and the difficulties, constraints and biases that must be meticulously addressed for the effective delivery of AI in the health-care sector.

KEYWORDS:

• Artificial intelligence
• healthcare
• biomedicine
• artificial neural network
• clinical diagnostic

Acknowledgements

Dr Jayanti Mukherjee would like to express my heartfelt thanks and gratitude to Dr T. Rama Rao, Principal, CMR College of Pharmacy, Hyderabad, who motivated her endlessly for this review write up. Dr Biswanath Bhunia, P Dutta and Ramesh Sharma express gratitude to Director, National Institute of Technology, Agartala, for encouragement and support.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

Compliance with ethical standards

This article does not contain any studies with human participants or animals performed by any of the authors.

Author contributions

All authors contributed to the study conception and design. Material preparation and data collection were performed by Jayanti Mukherjee [JM], and analysis was performed by Biswanath Bhunia [BB]. The first draft of the manuscript was written by Biswanath Bhunia [BB], Prasenjit Dutta [PD] & Ramesh Sharma [RS] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript

Additional information

Funding

No funding was associated with the research work presented in the manuscript.

Notes on contributors

Jayanti Mukherjee

Dr. Jayanti Mukherjee is working as a Professor and HOD in the Department of Pharmaceutical Chemistry, at CMR College of Pharmacy, Hyderabad, India. She obtained her B. Pharm, M.Pharm (Pharmaceutical Chemistry) and PhD in Pharmacy from Jadavpur University, Kolkata, West Bengal, India. She has more than 21 years of teaching experience and has more than 34 journals of national and international repute. She guided many post-graduate students, published a kindle edition on Clinical Research on Amazon platform, has a book chapter in her laurel, acted as a Principal Investigator in a research grant of Rs 6.1 L received from MPCST, Bhopal. Her area of interest lies in Phytochemical studies, Pharmacological studies, Biosensors and Artificial intelligence. She is also a life member of APTI and IPA governing bodies of India.

Ramesh Sharma

Ramesh Sharma is a Research Scholar in Department of Bio Engineering at National Institute of Technology Agartala, India. He obtained his Bachelor of Technology in Process and Food Engineering from Central Agricultural University Imphal, & Master of Technology in Food Engineering and Technology from Tezpur University.

Prasenjit Dutta

Dr. Prasenjit Dutta is an Assistant Professor in Department of Production Engineering at National Institute of Technology Agartala, India. He obtained his Bachelor of Engineering, Master of Engineering and PhD in Production Engineering from Jadavpur University. He has 8 years of industrial experience and 18 years of teaching experience. His area of interest incudes Advance Machining Processes, Optimization techniques and Artificial intelligence. He is also a member of Institute of Engineers, India.

Biswanath Bhunia

Dr. Biswanath Bhunia received a PhD in 2012 from National Institute of Technology Durgapur’s Biotechnology Program and Fast Track Young Scientist award from the Department of Science and Technology of the Government of India in 2012. Following completion of his PhD, Dr. Bhunia joined to academia as an Assistant Professor in the Department of Bioengineering at the National Institute of Technology Agartala in 2013. He is working on various secondary metabolite production using fungal, bacteria, cyanobacteria, algae etc. He has a total h-index of 30 and i-index of 55, with over 100 publications in international peer reviewed journals. He has also published several book, book chapters, and gave lectures at various international and national conferences, and seminars on topics ranging from bioprocess engineering, bioinformatics, enzyme and microbial technology, advanced purification process and modelling.