AI technology is transforming healthcare in a big way, especially in the context of health-related mobile apps and other medical tools to improve care. Rae Steinbach, Head of Product and Content at Blue Label Labs, an app development company, explores the reasons driving the growth and adoption of AI in healthcare, and its potential for transformative impact.
While its effects might not be obvious in your everyday life, Artificial Intelligence is changing the world around you in significant ways. It is affecting the ways people interact, and the products we buy and it is changing the ways businesses operate.
In the realm of healthcare, we are starting to see some of the ways AI can be integrated with healthcare software development and other medical tools to improve care or save lives with better practices for treatment and diagnosis. What makes this truly remarkable is that we are only just starting to see the potential.
With forecasts showing considerable growth, we should expect some exciting developments in the next few years. To get a better idea of what to expect from this future, let’s take a look at a few of the current trends for AI in the healthcare industry.
What’s Driving the Growth?
Besides the considerable investments being made in healthcare AI, there are significant tech trends that are helping to make this growth possible. The first is that modern technology is now making these developments possible. Some of these ideas may have existed in the past, but the resources to make them happen didn’t exist.
It requires a lot of computing power to run some of these advanced AI systems. In the past, this type of power was not accessible to most researchers. Now you have GPUs that are getting more powerful with every year and computing power is more accessible for researchers and businesses.
We have also seen major advances in Deep Learning. In the past, most AI programs were very simple. With the hardware and computing power becoming more accessible, it is now possible for businesses and researchers to develop and use Deep Learning algorithms to accomplish tasks of increasing complexity.
Finally, there are vast amounts of data that are now available. Medical records have gone digital and this makes it easier for AI systems to process and analyze the health information of large populations.
Here are some of the areas where AI can have the most transformative impact on healthcare management and delivery:
1. Better Diagnostics with AI
Artificial Intelligence has the potential to improve the process of diagnosing diseases. With human doctors doing the work, it can be a time-consuming process. Along with that, humans have limitations that can result in a misdiagnosis or a failure to detect an illness in its early stages.
With an AI algorithm that is trained to detect disease, a computer system can analyze and diagnose several patients in the time it would take a human doctor to diagnose one patient. Furthermore, these systems could be trained to detect diseases earlier and this could lead to a better outcome for the patient. In a review of the research, it has already been shown that a Deep Learning algorithm can perform just as well as a human healthcare professional for some diagnostic applications.
2. Medical Consultations
The idea of digital medical consultation has been around for a while. However, the early systems depend on a real human doctor working on the other end to ask questions and provide recommendations. With smarter AI systems, some of these consultations could be handled by a computer program.
As these systems improve, they will get better at knowing which questions to ask based on the patient’s previous responses. Thanks to advances in Natural Language Processing, they will also get better at understanding the feedback they get from patients. This type of system can then be used to help relieve some of the work from human healthcare professionals and this will allow them to focus their attention on patients that need their attention more.
3. Robotics in Healthcare
Robots are becoming more common in healthcare. This does not mean that you will have a robot doctor any time soon, but there are several ways robotic systems are being used to assist with treatment. We are now seeing robots used to automate some of the lab work that is used in medical facilities. You also have robots in physical therapy to help patients recover faster. Robotic surgery is helping doctors perform complex procedures with greater precision and less risk.
4. Drug Research
Outside of treating and diagnosing patients, AI is also helping researchers find and develop new drugs. Using Deep Learning, researchers will be able to feed these systems incredible amounts of data that can then be analyzed to find new treatments or recognize trends with existing drugs. This will not only help researchers to discover new treatments, but it could also provide information concerning which treatments are most effective or determine the best option depending on the patient’s medical history.
5. Digital Follow-Up Visits
Doctors are busy professionals, and they often do not have enough time to give each patient the attention they need. For many patients, follow-up care or checkups may be necessary, but this can take time away from patients who may need more of the doctor’s attention.
For patients whose follow-up care does not need the hands-on attention of a doctor, AI could provide an answer. Based on the patient’s history, an AI follow-up system would know which questions to ask. It could then analyze the responses to provide the patient with the correct recommendation. If there is a problem, the AI system will know to refer the patient to a human doctor for an in-person follow-up.
AI is helping doctors and other healthcare professionals be more efficient, it is working to discover new treatments and it is also improving the quality of care while making it more accessible. What makes this so amazing is that the technology is still in its early stages. With the expected market growth and development of the technology, we should expect to see some incredible advances shortly.
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