Research Paper on Artificial Intelligence in Healthcare

Abstract

Since time immemorial, the Universe has been plagued with sustained and significant challenges ranging from diseases, insecurity, unemployment et cetera despite it hosting some of the best brains of the human generation. Clearly and without a doubt, the challenges will stay longer with us even with the continued efforts to try and tame them. The demand today is evident for a different perception of human guided artificial intelligence approaches to develop more efficient, accurate, cheap and attainable solutions. The objective of this research paper is to underscore artificial intelligences' role in emergency health care as a functional treatment approach in attaining improved healthcare. The paper objectively explores the present use of artificial intelligence in emergency health care. It analyses information from literature retrieved mostly from primary sources that include previous research articles and journals. The paper discovers that artificial intelligence currently fills the Global void on the demand of patient health monitoring, consultation and treatment via different mobile apps. The mobile applications convey immediate feedback on diagnosed health related issues to the patients. Using artificial intelligence has been a tremendous success with lots of promising glances. Today, clinicians, doctors and other health officials can maintain appropriate healthcare even in the remotest communities. This has enhanced doctor-patient awareness and provided the necessary skills and knowledge to them. The merger of artificial intelligence in healthcare is definitely the future.

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Keywords: Artificial intelligence, health monitoring

Chapter One: Introduction

In the modern World, where PCs have been incorporated into our daily lives, it is hard to ignore the role that they play in the healthcare sector. The conceivable uses of innovation in healthcare are increasing rapidly, just like the extent of what those mechanical advancements can achieve. Computers currently can store, process and analyze patient data on a higher level than ordinary clinicians, making detections and giving prognoses of patients globally. This paper explores how artificial intelligence helps physicians, nurses and other health workers in modifying impersonal data into individualized service.

Bennett & Hauser, (2013) define Artificial Intelligence (AI) as a science and engineering field that deals with the numerical comprehension of responsible conduct, and with the formation of antiquities that show such behavior. According to Russell & Norvig, (2016), Aristotle strived to regularize argumentation through his philosophies that included three-part logical thinking. Most of the services witnessed presently are an inspiration of Aristotle's work as well as other previous studies. According to Rosenberg, Tripathi, & Blum, (2010), researches have been studying the possible uses of artificial intelligence in healthcare since the middle of the past century. They add that the use of AI innovation in the field of medical procedure was first progressively researched by Gunn in 1976 when he investigated the likelihood of diagnosing intense stomach pain with PC analysis. The past twenty years have witnessed a rush in the enthusiasm for AI in healthcare.

Challenges Facing the Study

Clinical adoption is one of the main difficulties AI in healthcare confronts. To appreciate its significance, the healthcare sector must put in place personnel that is enlightened about AI, so they are safe using it hence allowing the AI innovation to grow. Doctors and patients training on using AI is another challenge. Not every individual is privy to robotic information. This way, embracing AI innovation is a challenge that should be solved through training.

Problem Statement of the Study

In the modern World, the role of Artificial Intelligence in Healthcare cannot be ignored. The conceivable uses of innovation in healthcare are increasing rapidly, just like the extent of what those mechanical advancements can achieve. This paper seeks to explore how artificial intelligence can help physicians, nurses and other health workers to modify impersonal data into individualized service.

Research Questions

This research project seeks to answer the following research questions at the end of this study:

What is Artificial Intelligence in Healthcare?

What are the advantages and disadvantages of AI in healthcare?

Aims and Objectives

The primary objective of this research project is to examine Artificial Intelligence in Healthcare in the modern era. To establish the primary objectives, the researcher will explore the characteristics of AI during the past decades and the benefits and demerits associated with it.

Limitations of the Study

In this research project, secondary data was used to examine Artificial Intelligence in Healthcare. Therefore, there might be databases since the researcher depended on the already collected data.

Chapter Two: Literature Review

As per Copeland, (2017), Artificial Intelligence (AI) can mainly be defined as the procedure of creating frameworks established with the scholarly procedure aspect of humans, which include the ability to think, find significance, conceptualize, and gain knowledge from experience. Huge AI affiliated organizations such as Google and International Business Machines (IBM) are today involved in incorporating AI with health care via modern innovations and technologies. The main Artificial Intelligence Healthcare-associated programs currently comprise of Google's Deepmind Health and the development of Watson's IBM (Deepmind Health, 2017; Watson, 2017).

The United Kingdom's (UK) National Health Service (NHS) applies to Google's DeepMind program in diagnosing specific diseases using data collected by a mobile application. Furthermore, as per DeepMind Health, (2017) the UK's NHS also uses the program in analyzing medical images obtained from its patients to create computer vision algorithms that can detect cancerous tissues. Next, to that, Watson, (2017) adds that the IBM was developed to distinguish all types of data, ensure regular networking among individuals by human-robotic growth, gain knowledge and boost ability to reason. Suffices to say, Artificial Intelligence has four main elements that include: Understanding, Reasoning, Learning, and Interacting.

Artificial Intelligence can likewise be termed as "the science and engineering of developing robotic computer systems such as the IBM Watson that are capable of running errands independently," (Chen, Argentinis, & Weber, 2016). They add that the computer systems use distinct algorithms, decision-making abilities, and large data to give solutions or responses to applied instructions. Ahmed, Toor, O'Neil, & Friedland, (2017) argue that it is possible to connect data collected by mobile apps and social media with private patient records, Electronic Health Records, and genomics. Next, to that, they add that the aggregate of this data, i.e., "Predictive and Prescriptive Analytics" can be used to determine future forecasts and design situations by simulations and forecasts. This according to Chen et al., (2016), increases the ability to act on potential future health matters sometimes resulting in the true personalization of healthcare. "The speedy commercialization of big data analytics and machine learning has helped push Artificial Intelligence to the front line of healthcare and life sciences and is set to change how the industry detects and prognoses diseases" (Ahmed et al., 2017).

Dilsizian, & Siegel, (2014) argue that it is hugely significant to merge AI tools in daily medical uses to enhance effectiveness in treating patients and to avoid expenses by reducing the risks of misleading diagnosis. This they add advances better functional planning and minimizes the risk of occurring issues. Below is a summary of the reviewed information from literature.