Some people say that artificial intelligence is the electricity of the 21st century. In the same sense that discovering electricity shaped a generation, the potential for AI is huge and could cause shockwaves throughout many industries, healthcare included.
The definition of AI is the ability of a computer or computer-controlled robot to perform human tasks. The robot can make its own decisions just as a human can. Most of AI’s current trajectory involves a category of algorithms called machine learning. The algorithms (or computer processes for solving a computation problem) use statistics to find patterns in large amounts of data.
AI takes the patterns and make predictions on things such as music to suggest for you on Spotify or whether you have cancer based on an MRI.
While AI has gained significant traction within the healthcare industry, it’s safe to say robots won’t replace clinicians. AI will only assist clinicians in performing tasks more accurately and efficiently.
Over the years, we’ve seen AI expand within the healthcare industry to improve both the processes and tools in use.
For example, through AI technology, people with neurological diseases and trauma to the nervous system can begin interacting with others and move around with brain-computer interfaces.
Another example involves stethoscopes. Algorithms are being developed that combine a digital stethoscope with artificial intelligence software to help clinicians detect heart disease risk more accurately.
In this article, we will discuss:
- How AI is affecting healthcare practices
- How AI is affecting healthcare jobs
- Examples of AI in healthcare
- The future of AI in healthcare
How is AI affecting healthcare practices
AI is a digital companion for clinicians. It can provide endless resources and data to the field that healthcare workers need. Below you will find some of the ways that AI enhances healthcare practices.
AI provides clinicians with an opportunity to access immense data sets rather quickly. This information can prove life-saving to patients. AI analyzes data regarding treatment, prognosis, and speed of care for millions of patients at a time. Moreover, new technology can research and find patterns within data to help make diagnoses.
For example, AI can help clinicians detect diabetic retinopathy (the world’s leading cause of blindness) through image recognition. Google researchers have worked with algorithms to analyze retinas images and diagnose the disease with over 90% accuracy.
Beyond data, AI can analyze pictures as well. Due to the innovations within cloud computing and deep learning, some platforms analyze medical images exclusively. Some of the potential benefits include:
- 2D and 3-D imaging give important information on critical organs like the liver, heart, and lungs
- Provides more detailed diagnoses for medical images
- Scores medical images to determine disease
- Deep learning software decreases the time needed to complete medical imaging procedures
AI brings greater accuracy to the imaging field. In many ways, it provides greater accuracy than a human can. Beyond that, it helps speed up the process and allows clinicians to focus on more significant duties.
Automated workflow assistance
Healthcare workers often deal with lots of information for patients. Clinicians have to keep track of minute details regarding patient care, such as test results and medical images. This keeps them on a treadmill doing the same tasks over and over again.
AI can help manage many of these workflows and allow nurses to focus on more creative, patient-oriented endeavors. Nurses often prefer working with patients and less on purely administrative tasks associated with keeping track of information.
Telehealth and AI
Many patients today prefer receiving care from the comfort of their homes. Telehealth is a way to correspond with and monitor patients electronically. As such, AI plays a vital role in the development of telehealth. Machine learning can help patients with chronic conditions.
AI can recommend treatments for telehealth workers and analyze the current treatment regimen to determine if it’s the most effective.
These are just a few ways AI is impacting healthcare practices and making nurses’ jobs easier.
How is AI affecting healthcare jobs?
Though robots aren’t here to replace nurses anytime soon, AI impacts professional development, the job search process, job requirements, and more.
Professional development and education
In regards to professional and development, AI can help with the continuing education process and re-training of nurses. In fact, AI has already helped train a new class of nurses. Specifically, through virtual simulations, nurses can learn skills they would practice within the field.
According to Wolters Kluwer, 65% of nursing education programs have adapted virtual simulation. The programs provide hundreds of real-life scenarios along with health record use. Virtual sessions can include practicing urinary catheter insertion or dealing with an aggressive patient. These simulations will play a pivotal role in training nurses in the future.
Many employers utilize AI via recruiting software to screen job applicant profiles or resumes, and match them with appropriate opportunities. This makes the job search process more efficient for both sides of the market.
Additionally, AI’s use of algorithms helps social media function, and social media is a means by which nurses communicate and network frequently for both professional and personal purposes.
Examples of AI in healthcare
Though we have championed AI as the electricity of the future, it’s the electricity of the moment. Several institutions across the country are already using AI to enhance and augment medical practice.
Intelligent symptom checker
In Boston, clinicians within the infectious disease department use Buoy Health system. Buoy Health uses to check symptoms and cures with algorithms to diagnose and treat illnesses. Essentially, patients speak to a chatbot who interprets the patient’s symptoms and health issues and creates a care plan around its diagnosis.
This software allows clinicians to divvy up their workload and draw more sound medical conclusions about patients.
Pre-emptive cancer detection
The best way to defeat cancer is to catch it early, so the following program has helped the oncology practice significantly. Freenome uses routine blood draws on patients to detect early cancer signs. They can combine expertise in molecular biology and computer techniques to see patterns within billions of data points.
This AI tool will help make catching cancer diagnoses easier for clinicians in the long run and hopefully save lives.
AI-Powered radiology assistant
Within the radiology field, there’s a new method using AI to help augment the process. Zebra Medical Vision gives radiologists a sidekick that receives and analyzes imaging scans for clinical findings. These findings by the AI can help radiologists in making diagnoses.
The Future of AI in Healthcare
The future of AI in healthcare is boundless and most healthcare providers believe it’s going to improve their profession. According to a study in Frontiers in Artificial Intelligence, 79% of healthcare professionals thought that AI could be useful or extremely useful in their work. Only 10% were worried that AI would replace them at their job.
There are several pioneering systems in the works for AI. One of the more prominent cases is IBM Watson, which has made strides in oncology. The program analyzed genetic data to identify a rare form of leukemia that clinicians could not find.
On another project, the IMB Watson reviewed and provided treatment suggestions from genetic data of tumor cells in 10 minutes when it took human experts 160 hours to check.
Another significant development in AI that will shape the future is surgical robots. Generally, surgical robots work in conjunction with the human surgeon. However, in the future surgical robots may have the capacity to work alone on more complex surgeries.
Overall, AI has a chance to revolutionize the 21st century as a tool rather than a replacement for healthcare workers.