AI is making strides of development in various fields. And one of those fields is healthcare. From medical research to treatments, there are many areas in this sector where AI can contribute.
In this article, we’ll focus on some of the prominent areas of AI applications healthcare-based. Let’s get started.
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Applications of Artificial Intelligence in the Healthcare Industry
1. Drug Development
Drug development is one of the slowest processes in the medical field. It takes around 10-15 years to develop any new medicine. To put it differently, the drugs coming in the market in 2020 were in their early stages of development in 2007 or 2005.
There are many stages in drug discovery, due to which this process takes so many years. AI can help the researchers in streamlining many of these processes. With its use, researchers can develop new drugs faster and help people in getting better quality treatment earlier than before.
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Here are some ways AI is helping the medical sector in drug discovery:
Cancer Treatments with AI in Healthcare
Cancer is a harmful mutation of cells in the human body. And finding a cure for cancer has been one of the biggest challenges for the medical sector. Because cancer cells are initially a part of the body they are present in, it’s challenging to target them specifically. This is a significant difficulty which many organizations are trying to overcome all across the world.
AI is helping medical professionals to solve this problem in multiple ways. In the case of cancer, the earlier it gets diagnosed, the better are the patient’s chances of survival.
Cancer grows in multiple stages. AI can help doctors and medical professionals in identifying cancer at its early stages. Currently, doctors use biopsy, X-rays, and other conventional methods to detect cancer. Freenome uses AI for this purpose to enhance the accuracy of the test results.
With the help of AI, Freenome is giving a faster alternative for cancer screening. It allows medical professionals to identify cancer in its early stages through blood tests. They use immune- and tumor-derived signatures to identify warning signs of the disease. This helps in the prevention of its development as the doctor can then give the patient the necessary treatment.
Apart from that, we have BioXcel Therapeutics, a biopharmaceutical organization that’s using AI in drug development. AI helps this company in shortening development timelines, increase the probability of their success, and optimize the economics of research and development.
They are working on the development of an orally-available immunity activator that can help in the treatment of pancreatic cancer and a rare version of prostate cancer.
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Finding Cure for Rare Diseases
Rare diseases offer unique challenges to the medical sector. They are hard to find and have expensive treatments. AI can facilitate the finding of rare diseases and help the healthcare sector in overcoming the challenges they pose. Rare diseases are a massive problem for the medical industry. With around 7000 rare diseases affecting over 30 million people in the US, they lead to numerous dangers.
Clinicians face problems in diagnosing and treating the people affected with such diseases. And AI applications healthcare-based, are contributing a lot in solving those challenges.
A great example of AI’s help in solving these problems is BERG. It uses AI to map diseases and focuses on understanding the biological basis of a specific illness to help in making better and more precise drugs. BERG had released its findings on a treatment for Parkinson’s Disease in 2018.
Their results gained a lot of attention because they had discovered several links between the chemicals present in our bodies, which the scientific community was unaware of before. Another major highlight of their finding was that they had used AI to solve this issue.
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2. Better Patient Experience
Patient experience is one of the many reasons why people prefer to go to private hospitals over public ones. But what if your patient experience was optimal everywhere?
With the help of AI, clinics and hospitals can reduce the hassles a patient faces and optimize their experience. AI applications healthcare-based can help such facilities in enhancing their efficiency and the satisfaction of their patients:
Automation of Repetitive Tasks
A lot of administrative and organizational tasks in hospitals are repetitive. And even though they are simple, they require time and resources, which the staff can spend somewhere else. AI can solve this problem by automating most of those tasks.
When these become automated, it frees up time for the staff to focus on more critical areas of administration and organization. They can serve the patients better when they have more time and resources at hand.
If you’re wondering whether AI in healthcare is solving this problem or not, then take a look at Olive. Olive has an AI platform that helps healthcare professionals in handling mundane tasks, and enhances their productivity. A significant issue among healthcare professionals is burnout and inefficiencies. Olive AI is capable of 24/7. Moreover, while a human might be prone to making errors due to tiredness or fatigue, AI doesn’t make such errors. This way, productivity enhances further.
Olive AI is just one example of AI applications healthcare-based. There are many other ways AI can help this sector in automation.
3. Better Operational Flow
Ambulance delay is one of the leading causes of death for emergency patients. In Thailand, 20% of emergency patient deaths are due to traffic jams. It’s a global problem. Thailand isn’t the only nation that is trying to overcome this issue.
In India, around 30% of traffic accident patients die due to delayed ambulances. We can save hundreds of thousands of lives by solving this issue. And many experts are using AI for this purpose. AI is already a prominent solution in the transport sector. Google Maps uses AI to suggest fast routes from one place to another. We can use AI to help ambulances similarly.
And Qventus is doing just that. They are using AI to help hospitals in bringing their patients to the emergency rooms safely. It is capable of charting the fastest routes for ambulances, which they can use to reach the patients in time and save their lives. Qventus has many advantages, apart from delay prevention.
They help hospitals in patient management and allow them to decrease inpatient LOS. Many times, the transfer of patients get late because of management issues. Qventus helps the hospitals in reducing these delays, and so far, they have decreased such delays to up to 20%. By using data analytics and AI, Qventus is allowing hospitals to optimize their operational flows and enhance their efficiency.
John Hopkins Hospital in Baltimore, Maryland, is also using AI to enhance its operational flow. They are using predictive AI to manage the admission and discharge of patients. So far, they have improved their ability of patient admission by 60% with the incorporation of AI. Learn how artificial intelligence helps in pharma industry.
4. Personalized Healthcare
Every patient is unique. And so, their needs are unique too. And due to such needs, many patients face problems with their healthcare plans. Healthcare plans are generalized, so they can’t focus on the personal requirements of a patient. Not only does it lead to a loss of money for the patient, but it also causes monetary damage to the provider.
On the other hand, preparing personalized healthcare plans is quite tricky. To do so, you’d need to check the records of every patient and create a plan accordingly. This would take a lot of time, and people might not want to wait that long.
But while it’s increasingly difficult for human minds to create such plans, it’s rather easy for AI. Artificial Intelligence can go through tons of data points within a few minutes and analyze them at the same time. It can go through the medical records of the specific people and create personalized plans according to their needs.
The Cleveland Clinic is already doing it. They are using AI with health record data to create personalized plans for every person. This way, people will only spend money on the issues they want to be covered. It would save the finances of both the patients and the hospital. While it’s just limited to one clinic at the moment, the scope of AI in this sector is quite bright. And many hospitals and insurance providers might start using this solution in the future to provide better healthcare plans to the people.
4. Data Management and Mining
Medical facilities have tons of data. From medical records to administrative files, they handle a lot of data daily. Managing this much data is tedious and takes up a lot of time and energy.
By using AI, healthcare facilities can use their data to provide better services to their patients and enhance their management. Here are some ways how AI in healthcare is solving such issues:
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AI models, with sufficient training and data, can make accurate predictions. And the healthcare sector can benefit greatly from this ability of AI. That’s why many applications of AI in healthcare are focused on predictive analysis. One such use is risk prediction. Imagine if your doctor was able to predict your risk of developing cancer (or another severe disease) so you can avoid it? Wouldn’t that be great?
It could solve many problems in this sector, such as reducing the number of inpatient treatments as well as the number of critical patients. When you’d already know what you can do to avoid a particular condition to develop, you can do those activities and remain healthy.
KenSci is using AI for this purpose. AI applications healthcare-based revolve around predictive analysis, and KenSci is using it for risk prediction. Following are some advantages of risk prediction:
Early forecasts of diseases can help patients in getting treatments at lower prices. Preventative measures are always less expensive than the procedures of a particular disease.
This way, patients will get to save a lot of money. For example, if you were at the risk of developing diabetes, you can prevent it from happening. And this way, you’d save all the money you would’ve spent on its medication.
When hospitals would know who can get seriously ill, they’d provide those patients the required treatments. This way, the number of people getting critically sick would reduce substantially.
It would save the resources of hospitals as it would reduce the number of critical patients. Hospitals and clinics would get more time and resources to focus on their patients.
5. Planned ICU Transfers
We have already seen how AI can help hospitals and medical institutions with automation. By automating the repetitive processes, hospitals can save their time and resources. But apart from automation, AI can also use the data of an institution to streamline its workflow.
H2O.AI is using AI in healthcare to improve the workflows of the institutions and predict patients’ ICU transfers.
Research shows that unplanned ICU transfers lead to worse outcomes than the planned ones. These are only 5% of the patients, but they lead to 20% of the total hospital deaths. Such patients stay at least a week longer in the hospital and have higher mortality rates. Finding such patients is also quite tricky because the clinicians couldn’t recognize their symptoms easily.
This is where H2O.AI comes in. They use AI models to identify patients who have the highest chance to crash. Their algorithms and machine learning models consider the patient’s records, test results, and the vital signs to find warning signs. Their models work in realtime to help the hospital in determining which patients they should transfer to ICU.
Apart from ICU transfers, their AI solutions help hospitals and clinics in numerous ways, including predicting medical test results, and, as we mentioned earlier, improving the workflow.
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Numerous companies and startups are working on advancing the healthcare sector through AI. This field shows a lot of promise, and there’s much more we can do.
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What are the problems that occur while using AI in healthcare?
The field of medicine demands transparency and the ability to describe clinical decisions. The use of deep learning and other AI models in the healthcare sector is highly beneficial but explaining the models is quite a task. There are also certain ethical considerations that AI clinical applications confront, such as privacy concerns for data used for AI model training and security concerns while the implementation of AI in the medical field.
How does AI make healthcare less expensive in terms of time and money?
AI algorithms in the field of medicine are less expensive than traditional approaches. People no longer need to undergo a slew of costly lab tests owing to the use of AI technology in the healthcare system. This can be seen in the potential of AI in identifying biomarkers capable of detecting certain disorders in the human body. The algorithms ensure that the majority of the manual labor in specifying these biomarkers may be automated. In this manner, they save time which is very crucial in this field.
How does using AI empower patients?
Wearable technology, such as smart watches, is already being used by a vast number of individuals worldwide to capture daily health data ranging from sleep patterns to heart rate. When this data is combined with machine learning, it may be possible to successfully inform individuals whether they are at risk of certain diseases long before the risk becomes severe or untreatable. Currently, mobile applications give granular-level patient profile information, which may help patients living with certain chronic conditions better manage their disease and thereby live healthier lives. With this approach, AI has the potential to empower us to make better health decisions for ourselves.