Introduction
AI can be defined as computer software proficient of intelligent functions such as learning and analysis. It is a wide section at the cutting edge of technological advancement, growth and its changes every day. AI in the health sector is aimed at changing routines and approaches. AI is assisting to transform health sectors in different areas, for instance in management, administration and revenue cycle operations. In healthcare management, AI objective is to minimize errors since it is being relied upon to analyze data. In Administration, it aims at keeping health centre activities from flatlining and thus enabling day to day effective run of events (Ulziako, 2019). Lastly, AI can remodel healthcare trough revenue cycles. This can be achieved by identifying people and various activities and setting criteria for ideal operation
Emerging Uses of AI
AI in Mental Health - Today, one out four individuals suffer mentally and thus making it a principal cause of ill-health and disability. However, the integration of AI in healthcare systems can assist in the identification of mental symptoms. AI observe certain factors such as choice of words, phrase duration and the tone to study an individual (Contributor, 2019). Besides, the AI program (Wysa) is being used to help patients build mental resilience by chatting, monitoring, and helping users.
AI is medical imaging and diagnostics - AI has expanded extensively in the departments of medical diagnosis and imaging, which allow physicians and other medical researchers to deliver error-free clinical practices. Besides, AI has paved the way for quantification and uniformity through deep learning by preventing diagnostic errors and improving the results of medical tests. According to Ellahham (2019), AI has advanced the assessment in imaging to detect Diabetic Retinopathy (DR) and malignancy cases and has also helped in quantifying the movement of blood.
AI in data mining - Data mining is being employed to find insights and patterns from large databases. Currently, Health systems are applying AI to enhance detention systems by using clinical data (Derrington, 2017). The data is obtained by mining medical records in the health sectors.
AI in lifestyle management - Increased advancement in technology has allowed individuals to adopt digitization in managing their health at their comfort. Today, guardians are using AI in observing their infant's health, patterns of sleeping, growth and development (Ellaham 2019)
The Extent of AI Value in Clinical Practices
Early detection - In clinics, AI screening is useful in predicting the possibility of a person becoming ill. Primarily, it is being used mostly to recognize the chances of becoming ill of threatening diseases, for instance, cancer.
Identifying patterns - In hospitals, AI is used to identify trends, for instance, patients who are likely to miss appointments by using previous information to make judgements (White-Klososky, 2019)
Automating Processes - AI systems are being used to automate different processes such as data accumulation and processing
Making sense of large amounts of data - Electronic Medical records (EMR) rely on a considerable amount of data which contains vital information. As such AI is used in data mining to retrieve such information at the required periods (Ellahham, 2019)
Challenges of Adopting AI in Health Sectors
AI adoption in health sectors is in its initials stages, and then progress to the full adopted has been slowed by different factors. Some of the factors challenging the adoption of AI in health sectors include
Fear of losing Job - AI as a virtual nurse assistant is expected to perform similar roles a nurse would to enhancing patient care. Therefore, the adoption of AI would replace the nurses and render them jobless (Bresnick, 2019)
Privacy and big data problem - AI are used to detect trends by examining data from different medical regions. This is, however, prohibited by ethics in medical centres, and thus limiting the usefulness of AI in health centres (Bresnick, 2019)
Individuals do not trust AI - Most people favour views of real-life actors than those of machines. As such, lack of trust by the public challenges the adoption of AI.
References
Bresnick, J. (2018, August 6). Challenges of Developing and Deploying AI in Healthcare. Retrieved from https://healthitanalytics.com/news/challenges-of-developing-and-deploying-ai-in-healthcare
Contributor, C. (2019, April 29). How AI Is Revolutionizing Healthcare. Retrieved from https://www.forbes.com/sites/crowe/2019/04/29/how-ai-is-revolutionizing-healthcare/#34b63cf66850
Derrington, D. (2017). Artificial intelligence for health and health care. See https://www. health. gov/sites/default/files/jsr-17-task-002_aiforhealthandhealthcare12122017. pdf (last checked November 8 2018).
Ellahham, S. (2019, October 15). Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges. Retrieved from https://www.middleeastmedicalportal.com/application-of-artificial-intelligence-in-the-health-care-safety-context-opportunities-and-challenges/
Ulziako, C. (2019, June 9). How AI is Changing Healthcare. Retrieved from https://www.businessnewsdaily.com/15096-artificial-intelligence-in-healthcare.html
White-Klososky, A. (2019, October 18). Recent Research Utilizing AI For Early Detection Of Breast Cancer Has Doctors Rethinking The Human Role In Diagnosis. Retrieved from https://www.forbes.com/sites/cognitiveworld/2019/10/17/recent-research-utilizing-ai-for-early-detection-of-breast-cancer-has-doctors-rethinking-the-human-role-in-diagnosis/#3a72237744dc
Cite this page
Essay Sample on AI in Healthcare: Revolutionizing Health Sectors. (2023, Mar 07). Retrieved from https://proessays.net/essays/essay-sample-on-ai-in-healthcare-revolutionizing-health-sectors
If you are the original author of this essay and no longer wish to have it published on the ProEssays website, please click below to request its removal:
- A Statement of the Issues Being Researched - Health Care Ethics
- Prevalence and Treatment for Depression and Anxiety Among the Elderly
- Essay Sample on Managing the Multi-Generational Nursing Workforce
- Borrowed (Non-Nursing) Theories Applied to the Nursing Profession - Essay Sample
- Research Paper on Orem's Self-Care Deficit Nursing Theory: Enhancing Well-Being at Home
- Paper Example on Contingency Planning: Ensuring Employee Safety in Emergencies
- Report Sample on Management Concept in Health Care