Written by: Sasi Kondru
Email: sasi.kondru@gmail.com
Introduction
With several recent developments and breakthroughs, AI, or artificial intelligence, has become a part of several sectors, such as business, retail, and fast food. Recently, AI has started to become a part of the healthcare field as well, with many hospitals using AI to chat with patients, for medical transcription, and to help diagnose patients. In this article, we will take a look at how AI has become a part of healthcare, the positives and negatives of having AI in healthcare, and the future of AI in healthcare.
Figure 1. A futuristic visual on how AI can become a part of healthcare
How Has AI Become A Part of Healthcare?
AI has become a part of healthcare in several ways. AI has been used to help diagnose patients, improve communication between patients and physicians, and for medical transcribing.
Diagnosing Patients
AI can diagnose patients accurately by using large sets of images or other data to make comparisons and provide a diagnosis. For example, researchers at Stanford have developed an algorithm with an X-ray that can detect certain types of pathologies in a matter of seconds and Google has developed an AI that can diagnose diabetic retinopathy.
Communication
AI chatbots can help patients by answering simple questions, guiding them to physicians, and scheduling appointments. Since many of these chatbots are always available, a person doesn’t have to always be available to help patients, thanks to AI.
Figure 2. A conversation between a person and an AI chatbot
Medical Transcription
AI can quickly transcribe what patients are saying and even summarize and upload transcripts to a system. Additionally, AI can summarize medical records and make records more user-friendly for patients.
Figure 3. A doctor using medical transcription
Other Uses of AI in Healthcare
There are several other uses for AI in healthcare. For example, AI can be used to do paperwork, look at records, and organize data. Additionally, AI can be used by medical insurance providers to prevent fraud and approve and/ or deny people insurance.
Benefits of AI in Healthcare
There are several benefits to using AI in healthcare, mainly because of its accuracy and efficiency.
Since AI is trained with large data sets of other patient records, it can diagnose patients quickly and accurately (and sometimes even quicker and more accurately than an actual human). Additionally, since AI is a program, it does not have fatigue and feel stressed, which helps reduce errors and can produce outputs more efficiently. AI can even help patients reduce errors. For example, AI has been used to help make sure that diabetic patients are taking the right amount of insulin.
Additionally, since AI can be used to perform basic and mundane tasks, such as paperwork, healthcare workers will have more time for other tasks and can have more face-to-face time with their patients. This helps have shorter wait times and ensures that more time is spent by doctors on treating patients.
AI can also help reduce fraudulent activity in the healthcare sector. For example, AI can help detect unusual patterns in insurance history and insurance claims, which can prevent people from taking advantage of their insurance. AI can also reduce racial and ethnic bias when it comes to providing care and insurance.
Figure 4. How AI can be beneficial to healthcare
Drawbacks of AI in Healthcare
Despite how helpful AI can be for healthcare, it also has several drawbacks and risks, especially if not used properly.
While AI can be very helpful, it has to be trained with a very accurate data set. If AI is trained with a data set that has errors, then AI will make the same errors that it was trained with. AI also needs to be thoroughly tested before being used. For example, UnitedHealthcare, America’s largest healthcare provider, denied insurance to several qualified people and made many healthcare-related mistakes because its AI system, nH Predict, was trained with inaccurate data and made very inaccurate predictions. Because of the nH Predict system, an old woman who was paralyzed after a stroke was kept in rehab for 20 days, which is half the average for such stroke patients. Examples like this one show how AI can harm people if improperly used.
Additionally, using AI to collect data may affect data privacy and security, especially if the program used to make the AI was hacked. This has led to concerns about safety and trusting AI. Many people currently don’t trust AI. According to a poll, 60% of Americans would be uncomfortable if their physician used AI to diagnose them or recommend treatments and only 35% of Americans believe that AI would help lead to better outcomes.
People also fear that AI may take over their jobs. While a complete takeover of Ai is highly unlikely, it could replace several people in jobs relating to health administration and simpler tasks.
Figure 5: How Americans feel about AI being a part of healthcare
The Future of AI In Healthcare
AI is constantly being developed and advanced, and in the future, it may play an even bigger role in healthcare. Some ideas that people have come up with and companies have tested relating to AI and healthcare include creating complex robotic doctors and further using AI to help diagnose and treat patients. Many prototypes have been made for a robot doctor
Figure 6: Prototypes of a robot doctor
Conclusion
While AI continues to grow and develop in the healthcare field, it is important to understand both the benefits and drawbacks of AI in healthcare. AI has already become and may become a bigger part of healthcare, and it has the potential to revolutionize the healthcare industry.
Bibliography:
“America’s Largest Health Insurer Denying Care With AI That’s Wrong 90 Percent of the Time, Lawsuit Alleges.” Futurism, https://futurism.com/neoscope/health-insurer-ai-lawsuit. Accessed 7 Jan. 2024.
“Blog.” Datamatrix Medical, 30 Dec. 2023, https://datamatrixmedical.com/medical-transcription-blog/.
“Chinese Chatbot Uses AI to Provide Medical Diagnosis.” Springwise, 25 Nov. 2016, https://www.springwise.com/chinese-chatbot-uses-ai-provide-medical-diagnosis/.
Education, I. B. M. “The Benefits of AI in Healthcare.” IBM Blog, 11 July 2023, https://www.ibm.com/blog/the-benefits-of-ai-in-healthcare/.
Funk, Alec Tyson, Giancarlo Pasquini, Alison Spencer and Cary. “60% of Americans Would Be Uncomfortable With Provider Relying on AI in Their Own Health Care.” Pew Research Center Science & Society, 22 Feb. 2023, https://www.pewresearch.org/science/2023/02/22/60-of-americans-would-be-uncomfortable-with-provider-relying-on-ai-in-their-own-health-care/.
“Generative AI Will Transform Healthcare.” Bain, 3 Jan. 2024, https://www.bain.com/insights/generative-ai-global-healthcare-private-equity-report-2024/.
khan, Bangul, et al. “Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector.” Biomedical Materials & Devices (New York, N.y.), Feb. 2023, pp. 1–8. PubMed Central, https://doi.org/10.1007/s44174-023-00063-2.
Mark, Hannah, et al. “Yale Researchers Investigate the Future of AI in Healthcare.” Yale Daily News, 11 Sept. 2023, https://yaledailynews.com/blog/2023/09/11/yale-researchers-investigate-the-future-of-ai-in-healthcare/.
Nast, Condé. “Every Prototype to Make a Humanoid Robot.” WIRED, https://www.wired.com/video/watch/wired-news-and-science-how-engineers-design-a-humanoid-robot/. Accessed 7 Jan. 2024.
Oladele, Ayo. “Artificial Intelligence in Healthcare: Applicable Uses.” Velvetech, 21 Feb. 2019, https://www.velvetech.com/blog/artificial-intelligence-healthcare/.
Ronanki, Rajeev. “Author Post: Ethical AI in Healthcare: A Focus on Responsibility, Trust, and Safety.” Forbes, https://www.forbes.com/sites/forbesbooksauthors/2024/01/04/ethical-ai-in-healthcare-a-focus-on-responsibility-trust-and-safety/. Accessed 7 Jan. 2024.
“The (Robotic) Doctor Will See You Now.” MIT News | Massachusetts Institute of Technology, 4 Mar. 2021, https://news.mit.edu/2021/robotic-doctor-will-see-you-now-0304.
Kommentare