Week 8 Surfing the Tsunami

Surfing the Tsunami is all about beginning the journey of learning and exploring artificial intelligence (AI). For AI learning in general, there are some classes such as Coursera, Udacity, Khan Academy, or DataCamp. To be honest, I am a bit of a laggard in this area. Like a turtle, slowly but surely, I will get to where I am going. I use the technology advancements at work for the most part, and willingly learn when it is presented to me. However, I have not necessarily gone out of my way to learn about AI in the past. The three levels of learning are presented in detail: adapt, adopt, and adept. I am trying to be more comfortable with the adopt phase. The hands-on portion of making a website, a blog, Google Ads, Canvas, and looking into other AI platforms and companies was interesting. Most of it was slightly less intimidating once I sat down to figure it out. For work purposes, AI can be helpful, but if the system goes down, it is a nightmare and can be unsafe for patients. 

AI in healthcare is more in the form of advanced medical care procedures, testing, or outpatient follow up monitoring. The potential for AI in healthcare brings up multiple aspects and possible implications. One of the most common uses of deep learning involved recognizing lesions that could be cancerous in radiology images. There are also surgical robots to provide minimally invasive incisions, but the decisions are still made by surgeons. 'If-then' rules are used in electronic health records (EHR), however, it can be difficult to maintain due to medical knowledge changes and large amounts of data. Repetitive tasks can be automated such as updating patient records, billing, claims, and clinical documentation. Natural language processing can also be utilized to analyze clinical notes, transcribe, and conduct conversations. For those with speech difficulties, technological advances can help them communicate with others more easily. 

Patient follow-ups and continued adherence is one of the hardest battles outside of the hospital setting. In one study, more than 70% of responders reported having less than 50% of their patients engaged. There are technology options and monitoring that can help patients easily take care of their health from home. Some options include heart monitors, external defibrillators, blood pressure monitoring, and more. With all these AI advancements, there is some concern for job loss. One study showed that 35% of UK jobs will be lost over the next 10 to 20 years, but due to a variety of factors, the actual job loss may only be 5% or less according to some other studies. As of now, no jobs have been eliminated in healthcare due to AI. Those with direct patient contact will generally not have their jobs automated. Healthcare decisions have been made by humans in the past almost exclusively. AI can lead to ethical issues such as accountability, transparency, permission, and privacy. AI systems can help augment efforts for human clinicians to care for patients. There may be more focus on humans to focus on empathy, persuasion, and big-picture integration. However, there is a need to work alongside AI as changes progress in the medical field.