ORIGINAL RESEARCH Performance overview of an artificial intelligence in biomedics: a systematic approach Shashikant Patil 1 • Kalpesh R. Patil 2 • Chandragouda R. Patil 3 • Smit S. Patil 4 Received: 5 June 2018 / Accepted: 23 August 2018 Ó Bharati Vidyapeeth’s Institute of Computer Applications and Management 2018 Abstract Artificial intelligence and technological advancements are exceptionally influenced the entire society and mankind. Unprecendented and extensive use of social media, mobile phones and the internet has resulted in accumulation of huge amount of data. Most of this big data are available in unstructured form and it is beyond the capability of traditional systems to manage, maintain, supervise, keeping and analyse the data within a limited time span. Effective analysis and interpretation of health care data provides new insights in the condition of patients and suggest the most appropriate treatment opportunities. Discovery and invention of vital information in medical data helps the health care professionals to arrive at appropriate clinical decisions and improvement of quality of life in a variety of patients. In this article, we have discussed various issues and addressed them with the updated information on big data sources, big data man- agement, big data processing and big data analysis through various tools and techniques. We have also analysed and interpreted the recent applications and advancements in artificial intelligence and big data in the health care tech- nology and m-Health domain. Keywords Artificial intelligence Á Big data Á Big data analytics Á Health care Á m-health Á Machine learning 1 Introduction Artificial intelligence (AI) is a branch of Computer Science and Engineering that deals with the computational under- standing of intelligent behaviour and the creation of arte- facts exhibiting such behaviour [61]. The main idea of AI suggests the capability of learning and reasoning through a computerized system [23]. AI has the capability to analyse the complex medical data. It involves an understanding of mechanisms of intelligent behaviour and thought along with their personification in machines [23, 61]. As, AI finds the solutions of complex problems through the use of judgmental knowledge, it can contribute to medical prac- tice. The use of various AI tools and techniques implies the organization of knowledge in such a way that resembles the reasoning techniques of an intelligent human [66]. It is evident that there is a possibility of efficient analysis of medical data and making diagnostic predictions through AI [44, 61, 68]. AI is used in clinical setting either as clinical decision making expert systems or as a knowledge based systems implanted within laboratory instrumentation. Efforts have been made to develop the software architec- tures that imitate human intelligence [56]. Artificial neural networks, fuzzy logic systems and Bayesian belief networks are AI techniques that involve mathematical models based on human thinking and neu- ronal architectures. Rather than just making an assumption based on statistical distributions, AI tools generates the & Shashikant Patil sspatil@ieee.org 1 Department of Electronics and Communication, SVKM’S NMIMS, Shirpur Campus, Shirpur, Dhule, Maharashtra 425405, India 2 Department of Pharmacology, H. R. Patel Institute of Pharmaceutical Education and Research, Shirpur, Dhule, Maharashtra 425405, India 3 Department of Pharmacology, R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur, Dhule, Maharashtra 425405, India 4 Yardi Systems Private Limited, 2nd floor, Sigma House, Senapati Bapat Road, Pune, Maharashtra 411016, India 123 Int. j. inf. tecnol. https://doi.org/10.1007/s41870-018-0243-8