AI is not new to healthcare. Despite being a constant presence in the industry, there is a lot AI has to offer. It has the potential to not only revolutionize the whole healthcare industry, but it can also provide newer avenues of progress. Machine learning, alongside Deep learning, has already started shaping the healthcare of tomorrow. But is that all AI is for this sector? Dive in with us as we explore the impact of AI on healthcare and figure out how it is changing the industry daily.
Table of contents
Impact of AI on Healthcare
Starting with the present impact of AI, we will try to figure out why AI is so crucial to healthcare and the future implications. As far as we know, AI can improve healthcare significantly by simply streamlining the diagnostic process to provide better medical outcomes. And since it can also handle a vast amount of data quite easily, it can change the way we do research, clinical trials, or even treatment.
Given below are a few examples of how AI has impacted different components of healthcare over time:
Medical Examination
AI can automate image analysis to better aid diagnosis from CT scans and other medical devices. Once trained, it can help your garden variety radiologist with highlighting areas of interest for further inspection, saving time in the meanwhile. Prospects also hint at AI being able to freely read, understand and interpret medical scans without human supervision.
Tailor-made Drugs
AI already helps with medical research and clinical studies, but if we were to take it a step further, AI could also contribute to custom drug formulas and help discover newer treatment plans. Using data, we can train AI to target specific threats, such as the COVID virus. Data can also help AI understand the effect of present drugs on patients and how to counteract some of the side effects.
Risk Assessment
Historic data can get scoured to spot the telltale signs of a disease onset even before a trained eye can see one. And AI is better at handling data if nothing else. By figuring out the at-risk patients, AI creates a database that includes re-admission risks, those who have a high chance of returning for medical aid within 30 days of discharge. Many healthcare providers are actively using their patient’s EHR (Electronic Health Records) to track at-risk patients, to lower the costs associated with re-admissions.
Primary Healthcare
Many organizations have incorporated voice chat as a primary healthcare initiative to reach patients around the clock. Although they can’t do much over a voice or video call, it can still count as valid consulting, as any advice from a certified medical professional would be far better than random Google searches. We assume that the widespread acceptance of this tech would reduce unnecessary trips to a General Physician, helping patients with their medical bills. NPL is already being used in many organizations. It is only a matter of time when more powerful AI can also help with primary healthcare, if not, then at least help with the UI of the platform.
Benefits of Integrating AI in Healthcare
We have explained how AI has already impacted healthcare and nudged it towards a path of advancement. However, can we truly trust this tech? And if yes, then why? What is so great about AI and healthcare that we have to push for the cause? Given below are a few benefits to the healthcare industry cause of AI.
Faster Healthcare at a lower cost
AI will only aid healthcare cost reductions, as it lowers manual and repetitive labor. Furthermore, automating a process and analyzing data, which are both strong suits of an AI, will improve future results and reduce wasted effort, essentially lowering the overall cost of medical aid.
Admin automation
AI automation is not limited to core medical practices. It can also reduce paperwork by automating administrative duties such as form filling, pre-authorizing insurance, patient follow-up, unpaid bill prompts, and managing EHR. It will ultimately save both the administration and the patient money.
Early Detection
AI already aids in diagnosis. But it can also help patients directly by detecting diseases earlier than other tools, such as a mammogram, which has a high proportion of false positives. With an AI review and translation of mammograms, which is 30 times faster and 99% accurate, patients do not have to go for unnecessary biopsies. Then there is wearable tech, which paired with AI, can detect heart issues much earlier.
Diagnosis
IBM’s Watson is the best example of how AI can help with diagnosis. It is a huge database of medical knowledge that contains every medical journal, symptom, causes, treatment, and case study of responses from all over the world. Any doctor with such extensive knowledge at hand, and in real-time, will feel elated.
Treatment
AI also helps doctors and medical professionals with disease management by better coordinating treatment plans to help patients, even after their discharge. The tech helps doctors take a more comprehensive approach to healthcare.
Training
AI also aids soon-to-be professionals in their training by providing a naturalistic simulation, which yields more experience than other traditional methods. And the best part is that the training regiment will keep on improving itself with every successful batch as it will learn from older data.
Future AI Aspirations and Predictions regarding the Healthcare Industry
We are now at the last segment of the article, which lays down future expectations from AI and some possible predictions that might come true much sooner than later. These will highlight a route that the AI would take if it continues down the same path.
Better and personalized medicine
Although AI is already helping with drug discovery, the next big thing on the table is personalized drugs. Medicine is pure chemistry, and it reacts differently for different people. AI would be striving to edge out the seams and make a drug with minimal or no side effects, where it can be tweaked based on the patient’s condition. AI can also spearhead the discovery of newer drugs and treatments, and hopefully, it can aid with solving some of the most horrible diseases n the planet. And lastly, AI can even help with clinical trials, making them less of a trial-and-error process with a tighter control group.
Data Analytics
AI is already great at data analytics. However, developers predict it will take things a notch further with healthcare and create a real-time database to aid the whole medical process. Similarly, it can compile EHR to predict a trend that the researchers can safely focus on with priority. And while AI is already somewhat capable of early disease detection (in some cases), future expectations are the tech would be able to accurately identify at-risk patients with the specific condition and also present a targeted treatment plan.
Semi-Automated Surgery
And lastly, we have automated, well, semi-automated surgeries on the table. There are a few healthcare organizations that actively use surgical robots quite intensively during surgery. However, these are mostly manual and remote-operated. AI ought to change that. Another way AI can help is that it can read CT scans and MRIs to create a 3D model of a patient’s anatomy for the doctor to practice without any risks.