Analysis of Robotics, Artificial intelligence and Machine learning in the field of healthcare sector

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Abstract

Technological innovation or AI is enabled to determine the human's cognitive activities. ML, AI and automation processes made rapid changes in the pharma industry. The use of different analytic techniques helped to decrease the mortality rate worldwide. Uses of the AI tools help to determine the critical disease. Identification of genetic disputes is important for diagnosis and treatment. The growing technology helps to identify the dose errors in pharma companies. Currency analysis, frequent spectral analysis and the feature attraction process are necessary for Machine Learning (ML). Industry 4.0, ML considers the effectiveness of ML. Development of the intelligence computer programme is important for machine simulation. Moreover, it increases problem-solving skills in the pharma industry. The introduction sheds light on the entire project. The literature review has discussed the role of technological advantages in the medical industry. The impact of AI, ML and automation processes enhance profitability. The advantages and disadvantages of AI, ML and automation processes have been discussed in the literature review. In the methodology section, the secondary methodology has been chosen. Some inclusion and exclusion criteria have been concerned for the collection of effective information on the research topic. Cloud computing, cognitive systems and big data analysis, R&D process make huge changes in the pharma company. Increasing the use of the automation process provides safety and consistency to develop interconnectivity between the market demands, production rate of medicines. Recommendation and conclusion will be provided to maintain accuracy throughout the research paper.

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APA

Sarath Kumar Boddu, R., Ahamad, S., Pradeep Kumar, K. V., Ramalingam, M., Kirana Pallathadka, L., & Peniero Tupas, F. (2022). Analysis of Robotics, Artificial intelligence and Machine learning in the field of healthcare sector. Materials Today: Proceedings, 56, 2323–2327. https://doi.org/10.1016/j.matpr.2021.12.016

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