Research challenges and future directions towards medical data processing

ABSTRACT

Data in the healthcare industry and machine learning techniques is useful to analyse a huge amount of data to identify the hidden patterns in the disease, to give personalised treatment for the patient and also used to predict the disease. The main intent of this paper is to plan for a systematic review on medical storage systems, noise removal techniques for medical images and multi-disease prediction using artificial intelligence. This paper conducts a algorithmic contributions used for medical storage systems, noise removal in medical images and multi-disease prediction that are analysed. Moreover, the performance metrics measured in various contributions adopted tools, and different datasets utilised for solving those problems are surveyed. Finally, a strong research gaps and challenges that will pave the way for creating a room for future research perspective are explored. The suitable research gap is focused with the existing limitations in traditional medical storage systems, noise removal methods and multi-disease prediction models that could motivate the researchers to focus on developing new models. Thus, with a strong integration of biomedical and healthcare data, modern healthcare organisations can possibly revolutionise the medical therapies and personalised medicine

KEYWORDS:

• Health care domain
• medical storage systems
• noise removal techniques for medical images
• multi-disease prediction
• artificial intelligence
• machine learning
• deep learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Anusha Ampavathi

Anusha Ampavathi is a research scholar in the Department of CSE, KL Educational Foundation. She has 9+ years of teaching experience in both academics. Her research interests include AI&ML, Data Mining.

Vijaya Saradhi T

Dr.T.Vijaya Saradhi Professor in the Department of CSE, Sreenidhi Institute of Science and Technology. He is having 20+ years of teaching experience in both academics and research. He authored book chapters related to Data Structures. He was recognized as best teacher in emerging areas like Python Programming, Data Science and Machine Learning. He published and coauthored more than 30 research publications. He is working as reviewer for two journals. His research interests includes AI&ML, Big Data Analytics, IOT. He is senior Members in CSI.