7 Examples of Best AI & ML in Healthcare in Action – Overview
Healthcare has been improving across the world, improving living standards and life expectancy. One of the primary reasons for this is scientific advancements in clinical research, drug discovery, and medical devices.
Artificial Intelligence(AI) & Machine Learning(ML) applications have intruded on all sectors, and healthcare is no exception. The advantage this technology provides in healthcare is that it can eliminate errors that are caused by humans.
AI tools do not get tired or bored like humans and can perform complex surgeries with great precision. AI software tools can store a vast amount of healthcare data, analyze it and give insights, which can be very useful.
As we saw in the Corona pandemic, healthcare professionals had to work overtime to attend to the massive surge in cases in a short period of time. In such a scenario, AI & ML tools can help by taking care of routine and administrative tasks.
For example, RT PCR test samples could have been analyzed by robots and reports generated by AI tools.
In this blog, We will have a look at seven current Use Cases of AI & ML in Healthcare.
1. Disease Diagnosis
Most of the AI work till now has focussed on disease identification and diagnosis. AI is being used to evaluate DNA to diagnose illnesses; smartphone apps can detect concussions, blood pressure, hemoglobin levels, and newborn jaundice.
For Example, IBM Watson, a supercomputer, uses a combination of Machine Learning and Natural Language Processing for Cancer diagnosis and treatment.
2. Monitoring Drug Response
AI can collect data continuously and analyze it for drug response, which can be shared with Doctors and other healthcare professionals. Pharmaceutical companies are already using it for the initial screening of drug compounds and which drugs will work better for individuals based on their biology.
3. Robots as Surgeons
Robots have been used in manufacturing for several decades now. They are now also being deployed in the logistics, pharma, and healthcare sectors. Robots can perform complex surgeries with high precision and eliminate the chance of human errors.
Doctors monitor robots as the former perform surgeries, or they assist doctors during surgeries that require a high degree of precision. Robots are better than human surgeons as they can see much better by zooming in and out, performing minimally invasive incisions, and stitching wounds.
Robots are being used for Gynaecologic surgery, head surgery, and prostate surgery.
4. Monitor Epidemics
We have recently witnessed the Covid pandemic, which affected almost the entire world—monitoring such pandemics or epidemics which affect millions of people and require medication, quarantine facilities, and patient tracking is difficult. This can be achieved by using AI tools and machine learning.
It is humanly challenging to monitor such epidemics, pandemics, as millions of healthcare workers will have to solely dedicate their time to containing one disease.
5. Clinical Trials
Clinical trials conducted for new drugs and medical devices generate a lot of data. The use of AI & ML can reduce the time to analyze this data significantly.
As a result, Doctors and healthcare professionals get these devices & drugs for use much faster than earlier.
It can also help find patients who are fit to undergo these trials and recruit them for the trials. Thus, a lot of time that can be required to find the candidates for trials can be saved.
6. Analyzing Errors in Prescriptions
Thousands of people die across the world due to prescription errors. These errors are caused due to Electronic Health Records’ flawed interfaces, which are used by doctors. As they choose the wrong medicine from the drop-down menu or get confused with the dosing units.
Machine Learning can be very useful in such situations. A software can compare the prescription with previous records, and in case of deviation, doctors are alerted to review them. This can prevent serious consequences due to overdose or wrong medicines prescribed.
7. Training
AI can be used for simulation; wherein inexperienced doctors can train and hone their skills related to surgery or diagnosis. Natural Language Processing and AI can be used to generate a large base of medical scenarios, which can be used to train a novice.
Training can be continually adjusted based on the performance of the learner in the simulated environment. AI training can be done from anywhere, even while traveling or after a tricky case at the clinic.
Future of AI & ML in Healthcare
We are still in the early stages of utilizing AI for healthcare and need to fully understand its potential. The scaling of AI & ML in healthcare will take place in three phases, taking into account the current technology and trends.
Phase 1:
AI & ML will take over routine & repetitive tasks of healthcare professionals, which consume a lot of their time. Along with this, AI & ML will be increasingly used in radiology, pathology, and ophthalmology.
Phase 2:
Healthcare will shift from hospital-based to home-based care with remote monitoring and virtual assistants. This phase will make increasing use of Natural Language Processing.
Phase 3:
As AI & ML tools gather more data, Clinical Decision Support (CDS) will become more accurate. In this phase, AI & ML will achieve their true potential, with robotic surgeries becoming routine and precise diagnosis of diseases.
In a Nutshell…
In the coming decades, more Healthcare professionals will be needed as the number of medical care facilities increases across the world, especially in developing countries. This is when AI tools can augment the services of the healthcare sector.
However, it will take time before we can trust the technology altogether. It is very difficult to say in how many years or decades we will reach that level. Several large firms are investing billions of dollars to come up with software & hardware tools for the healthcare industry. This will ensure that the technology keeps evolving and becomes more accessible and accurate with time.
For now, we can use AI & ML as supporting tools for doctors and healthcare professionals. This makes the use of technology in healthcare advantageous for both the patients as well as professionals.
Author Bio:
Victor Ortiz is a Content Marketer with Good firms He likes to read & blog on technology-related topics and is passionate about traveling, exploring new places, and listening to music.
