Secondary research essay ( Final )

Artificial intelligence and health care

    The term artificial intelligence in healthcare is also known as the overarching term which helps to demonstrate the utilisation of software, AI as well as machine learning algorithms to take off human ability in solving complex health care or medical data, presentation, and analysis. This essay is going to explore the utilisation of artificial intelligence in the modern healthcare sector and how would AI push ahead healthcare into another level in the near future. The vast use of artificial intelligence in the health care sector is in the documentation. 

    In modern times, artificial intelligence technology is very influential in modern businesses, and it will be applied to healthcare and everyday life. The utilisation of artificial intelligence in the health care sector assists healthcare providers in many fields of the patient. Artificial intelligence is helpful in the healthcare field as it helps in the diagnosis and treatment application (Jabbari and Rezaei, 2019). AI is useful in advancing the use of immunotherapy for cancer treatment. The term immunotherapy is the technology utilised to cure cancer for bits of help in the treatment. AI has profited from the immune system and the artificial immune system has been of use in overcoming challenges such as intrusion detection, self-healing of robots, optimisation, and anomaly detection (Jabbari and Rezaei, 2019). While by utilising immunotherapy, the patient's body is capable by its immune system to kill malignancies. As immunotherapy in the form of artificial interlines, the patient would be able to overcome cancer (Matheny, Whicher, & Israni, 2020).

    But the oncologist still has a problem that by using this type of AI which patients will seek benefits as well as very few numbers to people respond to current immunotherapy options. The other way of working with artificial intelligence in the healthcare sector is developing the next generation of radiology tools (Davenport, & Kalakota, 2019). While the radiological images id gained through the X-rays, MRI machines, and CT scanners which describes the inner working of the human body in term of invasive visibility (Davenport, & Kalakota, 2019).  However, radiology is applicable in all types of diagnostic processes, although many processes still depend on biopsies which is the process of sampling of tissues that may carry chances or risks including the swear infection. On the other hand, also it helps to enable the next generation of radiology tools which are detailed as well as accurate to change the tradition or process of tissue samples in a few cases. Moreover, artificial intelligence will help in mitigating the influences of severe deficits to take over the diagnostic duties related to humans (Davenport, & Kalakota, 2019). 

    This essay illustrates that artificial intelligence has been providing the main bedrock which helps in the development of clinical tools as well as it is powering predictive analytics. In my point of view, I strongly believe that AI should be utilised more in the healthcare sector, because it will push ahead modern studies in healthcare in general into another level of success. However, artificial intelligence has been developing the sense to manage the many critical conditions like sepsis and seizures which has been required in intensive analysis of highly compound datasets (Yu, Beam, & Kohane, 2018). AI will help in machine learning which may assist in the decision-making for a critically ill patient, for example, a patient who has a cardiac arrest and then entered in the comma.

References:

• Jabbari, P. and Rezaei, N., 2019. Artificial intelligence and immunotherapy. Expert Review of Clinical Immunology, 15(7), pp.689-691.
• Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94.
• Matheny, M. E., Whicher, D., & Israni, S. T. (2020). Artificial intelligence in health care: a report from the National Academy of Medicine. Jama, 323(6), 509-510.
• Yu, K. H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719-731.