Use cases of artificial intelligence in healthcare – there are many.
Today, many technology vendors, such as mobile app development companies have started to utilise the power of AI by creating applications that profoundly impact healthcare.
Using platforms of popular tech giants such as Google, Microsoft, Apple, IBM, Amazon, etc. these companies have successfully deployed many applications which are helping medical institutions across the world.
AI and machine learning needed to improve the healthcare industry
Popular use cases of artificial intelligence in healthcare
1. Virtual assistance in healthcare
There are a tremendous amount of health apps available on App Store and Play Store. According to Statista, by the end of 2019, the total smartphone users will reach more than $2.7 billion globally. And, all of them will have either of the voice assistants mentioned above. A combination of these voice assistants and healthcare apps can help customers to deliver medication alerts, educational material and more. This level of personal assistance can help people to live a healthier life without a human caretaker.
2. Research and advanced analytics
A majority of today, healthcare has become dependent on machines. Whether it is for a regular checkup or significant operations, machines have become a way-to-go for doctors to help their patients live a healthier life. For a majority of the times, machines and equipment work fine, but even they require maintenance and repair.AI can help technicians to detect the fault beforehand so that machines don’t fail at the time of emergencies. Apart from this, AI can also assist surgeons to perform surgery by providing them with information about the patient’s body part, which requires surgery. It also helps doctors to create highly personalised treatments for their patients. For example, IBM Watson’s AI has the capability to process unstructured as well as structured patient data and present evidence-based treatment alternatives for cancer patients.
3. Life coaching for personal health
Follow-ups are an essential part of healthcare, especially if a patient is suffering from a chronic disease. In a majority of hospitals and clinics, doctors offer regular follow-up or life coaching as a part of their treatment. However, such services can be extremely costly, and not every patient can afford it. But, unique wearable technology and an AI-enabled mobile app can help solve the problem. It will capture the data coming from the wearable device and suggest the required medication, exercises, activities, and even habits, which will help them live a healthier life.
4. Healthcare bots
It is evidential that very soon chatbots are going to replace phone call-based customer service altogether. Chatbots in healthcare can help patients to resolve their concerns faster than traditional counselling sessions with health care service providers. Bots can help a patient to schedule a follow-up instantaneously. Besides this, bots can also help patients to pay their hospital bills in a few clicks. To conclude, bots can help healthcare service providers to improve 24/7 customer service and assist patients by processing every service request faster, starting from scheduling an appointment to paying bills.
What’s the biggest barrier to AI adoption in healthcare?
5. Diagnostics assistance and medical imaging
Medical imaging has brought revolutionary changes in providing healthcare services by providing a better picture of various anomalies. But sometimes, the anomalies are so small in size that a human eye becomes unable to detect it. With doctors not being able to detect such abnormality can even cost a patient’s life. AI helps in detecting such anomalies which human eye cannot detect.
6. Dictation assistance
We have seen health care professionals browsing through various documents all the time so that they do not miss any detail while diagnosing patients. Missing a single detail can cost life to a doctor.
Natural Language Processing (NLP) can help doctors to filter out relevant information from lengthy reports. NLP not only allows doctors to filter out relevant information but also helps them by narrating that information to them so that it becomes easier for doctors to consumer information.
7. Drug creation
The pharmaceutical business is a billion-dollar business today. Costly medicines are often a result of rigorous research and development. AI can help reduce the cost of medicine by reducing the cost of R&D. In 2014, Atomise launched an AI-powered program, which was used to find alternative medications to the ebola virus. This program found to drugs which had the potential to reduce the effects of Ebola within a day. It reduced months of R&D work, which saved medical institutions time, money, and efforts to provide medicines to the people in need.
8. Cyber security
Hospitals and clinics hold a lot of confidential information. This information needs protection from cyber attacks. Even the smallest data leak can cause significant harm to both patients as well as healthcare centres/professionals. It might not be possible for the hospitals’ cybersecurity teams to figure out every potential threat to their systems. AI can help cybersecurity teams to figure out every potential issue or risk. The algorithm can also rank them based on their priority and present it to the team.
9. Fraud detection
According to Gibson Dunn, the total recovery amount that the federal government paid under the FCA was $2.9 billion in the 2018 fiscal year. This amount has increased compared to the previous fiscal year. AI can help prevent these fraudulent activities by learning from past events. The machine learning algorithm proactively searches for fraudulent claims and sends alerts to the concerned person as soon as they detect one.
10. Healthcare system analysis
Unnecessary hospitalisation has led many people to run into debt. However, new AI-based systems can help patients to identify workflow inefficiencies and mistakes in treatment.
Being a CTO for a healthcare technology company
According to Frost and Sullivan, the AI market in healthcare is predicted to reach $6.6 billion by 2021. Compared to other markets, the tech has made little progress in the industry – however, in the upcoming years, when the cost of mobile app development using emerging tech will reduce, a revolutionise will take place; from clinical support to maintaining security and integrity.