Role Of Artificial Intelligence In Healthcare Industry

Benefits of Artificial Intelligence in Healthcare

The healthcareindustry is ripe for a different transformation. From chronic diseases and cancer to risk assessment and radiology, there is a never-ending opportunity to leverage the technology to organize more efficient, defined and impactful interventions at precisely the right instant in a patient’s care.Patients demand more from providers and the amount of existing data continue to gain an incredible rate. In this way, artificial intelligence is used as an engine that drives the improvement across the care continuum (Alvesson&Sköldberg, 2017). 

AI provides a high amount of benefits as compared to conventional analytics and clinical decision-making tools. Learning algorithms can develop into a more precise and accurate way because they communicate with training information, and permitting individuals to increase unprecedented awareness into the diagnostics, treatment variability, care procedures,and patient outcomes.

Moreover, radiological images created by CT scanners, MRI machines, and x-rays provide non-invasive transparency into the internal performance of the individual. However, there are different diagnostic procedures that would depend on the physical tissue samples collected through biopsies. It creates risks such as the potential for the virus. Artificial intelligence would competent the next generation of radiology technique that is feasible and detailed enough in terms of replacing the requirement for tissue sample in certain cases. It is also assessed that inadequacy of trained healthcare staffs such as radiologists and ultrasound technicians can limit the access to life-saving treatment in developing regions in around the globe. In this way, artificial intelligence can aid to avoid the impact of the deficit of qualified clinical employees by allocating the certain diagnostic responsibility to humans (Dimitrov, 2016). 

The main aim of this investigation is to address the role of artificial intelligence in the healthcare sector. Following are the objectives of this research that helps to attain the main aim of this research:

RO1: To explore the meaning and concept of Artificial intelligence in the healthcare industry

RO2: To address the role of artificial intelligence in the healthcare sector

RO3: To recommend the ways of using Artificial intelligence in the healthcare industry

Following are the research questions that would aid to complete the research in a systematic manner:

RQ1: What are conceptual understandings about artificial intelligence in the healthcare industry?

RQ2: How artificial intelligence can influence the performance of healthcare industry?

RQ3: which strategies could be effective for successfully implement the Artificial intelligence in the healthcare industry?   

The research mythology section plays an imperative role in collecting feasible information with respect to the current matter. There are many methods that are considered in research methodology like research approaches, research strategies, research design, data collection, data analysis method, sampling method, ethical consideration, and research limitation. These methods could enablethe researcher to conduct research systematically and get areliable outcome in the context of the current matter (Elhoseny, Abdelaziz, Salama, Riad, Muhammad, &Sangaiah, 2018). These methods are discussed below:  

Radiology and Artificial Intelligence

Research approaches are imperative for conducting the research issue. There are certain approaches that could are considered in the research like inductive and deductive approach.

In this research, the researcher will use the inductive approach facilitates the researcher to conduct the research appropriate and get a feasible result. The inductive approach is effective for collecting theoretical data with respect to about research issue. The deductive approach will not be practiced by the researcher because it supports to make a hypothesis for conducting the research and get a reliable result. The inductive approach is practiced for collecting theoretical information about research issue (Hamet& Tremblay, 2017). This approach is also known as the top-down approach and it is appropriate with positivism philosophy.  It would lead to getting reliable information in the context of research issue. The inductive research is also effective for collecting data and aids researcher to create an approach for the study. Moreover, it is known as the bottom approach to applying with interpretivism philosophy.  The inductive approach allows examining collected data in depth and supports to get information with respect to the current issue. This approach facilitates the research scholar to collect a huge amount of information with respect to the role of Artificial intelligence on the performance of the healthcare sector. It facilitates to determine the relationship between consumer loyalty and deceptive advertising. Moreover, the deductive approach also supports to concentrate on examining the quantitative information that makes it inappropriate for this research study.  Thus the deductive approach is not practiced by the researcher to meet the aim of research (Patel& Patel, 2016). 

The strategy of research study facilitates the investigator for getting reliable information regarding research matter. There are several strategies that are practiced by the company such as literature review, survey through a questionnaire, case study, and content analysis. Research strategy could be prominent for accumulating the relevant data towards the research issues. Research scholar would utilize a content analysis technique to achieve the aim and objectives of research concern. It enables the researcher to attain the aim of a research study in minimum time. Accumulation of fresh data with respect to research dilemma is not required due to this research scholar would not execute a survey through questionnaire method. Research scholar would use literature review method and content analysis technique for attaining the feasible information towards the research dilemma (Shukla, Lakhmani, &Agarwal, 2016, April). The research strategy is the systemic method of data collection that ensures data availability for accomplishing objectives of effectively. In this research, research will imply a survey through questionnaire method and literature review to collect the information about the research issue. Survey through questionnaire tool is effective for getting opinion and views of the research candidate towards the research issue. Apart from this, the literature review approach is an effective tool for obtaining conceptual information in the context of the current issue (Silverman, 2016). 

Deficit of Trained Healthcare Staff and Artificial Intelligence

It is another section of research design this is practiced for accomplishing the aim and objectives of the research issue. Qualitative, quantitative, and mixed methods are considered in the research design. The qualitative research is effective for developing the understanding of specified research issue. This tool emphasized many factors such as opinion, thoughts, and language as it would be imperative to make a reliable decision. Moreover, the qualitative research design could consider many methods like a focus group, questionnaire, interview, and experiments. In this research, the mixed data collection method will be practiced by the researcher to conduct the research as it would decline the overall quality of the research outcome (Wong&Bressler, 2016).

The data collection is imperative for collecting information about the research issue. There are two kinds of methods that are considered in the data collection method like primary and secondary data collection tool. Moreover, the primary data collection method is an imperative tool for obtaining information about the research issue. There are certain sources that are considered by the research scholar to obtain sources like interview method, observation method, and survey through questionnaire method (Brewster, Chung, and Sparrow, 2016). Moreover, the survey through questionnaire method is an imperative tool for collecting views of the research candidates towards the current research matter. It would also be imperative for solving the research issues and meet the aim and objectives of the research issue (Fortino, Guerrieri, Russo, andSavaglio, 2014, May).

A data analysis tool is an imperative tool to examine the collected information and get a favorable result. There are certain sources that could be imperative for systematically evaluating the data and get areliable outcome in the favor of the research issue named Ms-Excel software and literature review method to evaluate the data. In this, Ms-Excel software will be practiced for evaluating the factual information about research issue (Fan, Yin, Da Xu, Zeng, Y. and Wu, 2014). Apart from this, it is also evaluated that research the literature review method will be practiced by the researcher to evaluate the theoretical information to reach at the valid conclusion (Burns, Luckhardt, Parlett, and Redfield, 2014).  

Research purpose assists the investigator to enhance and refine their understanding and knowledge with respect to research concern successfully. On the basis of the research,problem, nature research scholar could utilize explanatory, exploratory and descriptive. Exploratory research supports the research scholar to discover somewhat innovative but it does not provide a certain and valid key to the investigation problem. Beside this, descriptive research is practiced to elaborate and evaluate the performance and features of research participants that considers their perception, beliefs, approach and other imperative factors which are associated with research study (Cambriaand White, 2014). There isa certain purpose consisted in the descriptive research such as explaining, validating and describing. Different research findings which are efficiently practiced in the depth evaluation of research dilemma. Moreover, explanatory research is practiced to describe the research concern in the context of varied and various variables. Research purpose is also utilized to find out reasons and consequence of relationships among various variable that is needed to describe for obtaining the objectives of the research study. Exploratory research is chosen by the research scholar for this dissertation as it facilitated them to evaluate the solutions related to the role of artificial intelligence in the healthcare industry.  In this dissertation, explanatory research is not practiced as it is relied on earlier experience without including the present experience (De Vasconcelos, Gouveia, and Kimble, 2016).

Objectives of the Research

There are certain resources that could be considered by a researcher at the time of conducting the research as it is discussed bythe following table:

This research would be beneficial for understanding the conceptual aspect related to artificial intelligence in the healthcare industry. This investigation would be advantageous to comprehend the role of artificial intelligence in the healthcare industry. It would be helpful for understanding the pros of using artificial intelligence in the healthcare industry. This would help to comprehend the ways of practicing artificial intelligence in the healthcare industry.

It can be concluded that the researcherfaces many problems at the time of performing the research. Therefore, it is examined thatthe researcher will focus onthe systematic way of practicingArtificial intelligence and declines probabilities ofthe healthcare issue. Moreover, the investigator would be capable to obtain reliable data in the least time cost in the context of research matter. It can also be summarized that the mixed data collection method could be imperative for conducting the research by collecting factual and theoretical information in the context of a research issue. 

References

Alvesson, M., &Sköldberg, K. (2017). Reflexive methodology: New vistas for qualitative research.USA: Sage.

Brewster, C., Chung, C. and Sparrow, P., 2016. Globalizing human resource management.Routledge.

Burns, H., Luckhardt, C.A., Parlett, J.W. and Redfield, C.L. eds., 2014. Intelligent tutoring systems: Evolutions in design.Psychology Press.

Cambria, E. and White, B., 2014. Jumping NLP curves: A review of natural language processing research. IEEE Computational intelligence magazine, 9(2), pp.48-57.

De Vasconcelos, J.B., Gouveia, F.R. and Kimble, C., 2016, July.An organisational memory information system using ontologies. In Atas da Conferência da Associação Portuguesa de Sistemas de Informação 3( 3), pp.8-11.

Dimitrov, D. V. (2016). Medical internet of things and big data in healthcare. Healthcare informatics research, 22(3), 156-163.

Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., &Sangaiah, A. K. (2018).A hybrid model of the internet of things and cloud computing to manage big data in health services applications. Future Generation Computer Systems, 86, 1383-1394.

Fan, Y.J., Yin, Y.H., Da Xu, L., Zeng, Y. and Wu, F., 2014.IoT-based smart rehabilitation system. IEEE transactions on industrial informatics, 10(2), pp.1568-1577.

Fortino, G., Guerrieri, A., Russo, W., andSavaglio, C., 2014, May. Integration of agent-based and cloud computing for the smart objects-oriented IoT. In Computer Supported Cooperative Work in Design (CSCWD), Proceedings of the 2014 IEEE 18th International Conference on (pp. 493-498). IEEE.

Hamet, P., & Tremblay, J. (2017).Artificial intelligence in medicine. Metabolism, 69, S36-S40.

Patel, S., & Patel, H. (2016).Survey of data mining techniques used in healthcare domain. International Journal of Information, 6(1/2).

Shukla, S., Lakhmani, A., &Agarwal, A. K. (2016, April).Approaches to artificial intelligence in biomedical image processing: A leading tool between computer vision & biological vision. In Advances in Computing, Communication, & Automation (ICACCA)(Spring), International Conference on(pp. 1-6). IEEE.

Silverman, D. (Ed.). (2016). Qualitative research.USA: Sage.

Wong, T. Y., &Bressler, N. M. (2016). Artificial intelligence with deep learning technology looks into diabetic retinopathy screening. Jama, 316(22), 2366-2367.

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