This article explores the role of artificial intelligence in transforming the healthcare sector. It discusses how AI improves medical diagnostics, clinical decisions, and healthcare management.
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Running Head: ARTIFICIAL INTELLIGENCE IN HEALTHCARE Artificial Intelligence in Healthcare Name Institution
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ARTIFICIAL INTELLIGENCE IN HEALTCHARE2 Artificial Intelligence in Healthcare Introduction The artificial intelligence (AI) purposes to mimic human cognitive roles. AI has the potential to improve the health outcomes by growing accessibility of healthcare data plus fast development of analytic methods. There is no doubt that the artificial intelligence (AI) will play a crucial in transforming the healthcare. It is improbable that computers, as well as robots will completely replace physicians and nurses, but AI cannot be underestimated in its endeavours to transform the healthcare sector (Mesko, 2017). AI will not only predict outcomes plus improve diagnostics, but it will also change the manner the healthcare providers reasoning concerning how to provide safe and quality care to their clients. The paper will argue that artificial intelligence will play a crucial role in transforming the healthcare sector. Improving Medical Diagnostics Diagnostic errors are grave risk to safety and quality in the healthcare sector. It has been approximated that the frequency of outpatient diagnostic errors is around 5.08 per cent in the United States (US) that is about 12 million annually. AI has been used to advance the quality, as well as safety of health diagnosis, particularly in radiology because of the huge capacities of medical imaging data. Artificial intelligence has the capacity to improve diagnostics and eliminate the problems of misdiagnosis in the healthcare sector (Kim, Cho & Yoon, 2015). Fast research plus cross-referencing of data through AI will result in better diagnosis of diseases. The results as well comprise handwritten notes, geospatial and sensor data plus test results. The AI will totally revamp the negativities of scanning machines through offering greatly accurate inputs
ARTIFICIAL INTELLIGENCE IN HEALTCHARE3 of the patient body. The diagnostic team, the pathologist, and physicians may reach unanimous decision on the mode of treatment, and chances of overpowering diagnostic challenges are very high. For instance, using deep learning algorithms, AI will enable diagnostic team to distinguish between cancerous and non-cancerous cells in much more precise way. Dawes, de Marvao and Shi (2017) lately published a magnetic resonance imaging-focused algorithm of cardiac movement, which permitted the authors to precisely forecast the outcomes of patients with pulmonary hypertension (Dawes, de Marvao & Shi, 2017). Clinical Decisions With the swift advancement of medical tools, novel research data have been generated quicker through AI systems. AI would offer much of the bedrock for medical evolution through powering predictive analytics plus clinical decisions support tools, which clue physicians into problems long before they can otherwise acknowledge the need for an action. The quantity of data in the medical field usually doubles every three years (Curioni-Fontecedro, 2017). It is forecasted that if a doctor needed to remain completely relevant, the doctor need to read 29 hours per working day, which means it is not feasible top depend only on humans to keep the information. Thus, AI will help physicians make informed and effective decisions on clinical issues. With the machine learning plus natural language processing capacities, AI will assist doctors appraise patients’ electronic health records and additionally search-related medical research publications in addition to the guidelines. In addition, AI can offer earlier warnings for conditions, such as seizures that often need intensive analysis of significantly multifaceted datasets (Krittanawong, Zhang & Wang, 2017).
ARTIFICIAL INTELLIGENCE IN HEALTCHARE4 Healthcare Management The present systems in health sector concentrate on treatment-focused care that cannot offer suitable low-cost interventions for patients. The artificial intelligence provides an opportunity for the healthcare sector by monitoring healthcare platforms into health management networks to lower the growing costs in addition to enhance healthcare results. AI has been instrumental in promoting the management of healthcare system through reducing the costs and enhancing quality of care (Guo & Li, 2018). The introductions of the AI technology into the healthcare management systems can assist identify unnecessary diagnoses plus treatments. Currently, over testing and overtreatment are common in the healthcare settings that could be resolved through the introduction of AI. Therefore, this medical technology not only concentrates on the standard relations between patients and physicians, but too may be utilized in the management of healthcare systems for large companies. The AI can manage healthcare costs, cost recovery, and reactions to treatment (Mesko, 2017). Conclusions Artificial intelligence has the potential to enhance the accessibility of healthcare access, as well as the quality transforming the healthcare industry. It is a fast growing computer technology, which has started to be extensively utilized in the healthcare environment to enhance the expert degree along with the efficiency of clinical work, diagnosis, management of healthcare systems and make informed decisions to promote outcomes of the care and treatment. The future of artificial intelligence technology will be the future of the healthcare sector as it has already been successful.
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ARTIFICIAL INTELLIGENCE IN HEALTCHARE5 References Curioni-Fontecedro, A. (2017). A new era of oncology through artificial intelligence.ESMO Open. 2(1):e000198. Dawes, T.J.W., de Marvao, A. & Shi W. (2017). Machine learning of three-dimensional right ventricular motion enables outcome prediction in pulmonary yypertension: a cardiac MRI imaging study.Radiology. 283(11):381–390. Guo, J., & Li, B. (2018). The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries.Health equity. 2(1):174–181. Kim, H.S., Cho, J.H. & Yoon, K. H. (2015). New directions in chronic disease management. Endocrinol Metab (Seoul).30(2):159–166. Krittanawong, C., Zhang, H & Wang, Z. (2017). Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 69(3):2657–2664. Mesko, B. (2017). The role of artificial intelligence in precision medicine.Expert Rev Precis Med Drug Dev. 2(1):239–241.