Especially during the pandemic, AI has played a significant role in accelerating the vaccine development process, reducing the workload of healthcare staff, and providing remote and proactive healthcare for patients
It has been nearly two years since the first case of COVID-19 was detected, and ever since the outbreak, healthcare companies like Pfizer, Moderna and Bharat Biotech have been on the run to develop a vaccine to fight the virus. What’s interesting to note here is that especially in this period, AI has played a greater role in accelerating the vaccine development process.
To put in perspective, drug discovery typically takes years, and is an expensive affair. Aside from the operational costs and multiple stages of approval involved, one of the time-consuming processes is analysing billions of molecules and identifying how they can be used to do chemical binding to the target protein. Researchers will take years to do this manually, whereas AI has played a significant role in automating this process, thus reducing the time-taken to half or less. Similarly, AI has also been used in analyzing which drugs are likely to work (as opposed to companies performing multiple clinical trials), and bringing digital technologists and scientists together to work on developing drugs quickly and more effectively.
In the first article in the AI in Healthcare series, we looked at the challenges healthcare companies are facing with AI adoption. Use cases like the above show us that the technology can still prove to be effective in certain areas of healthcare, a topic we will be exploring in this blog.
AI in Robot-Assisted Surgeries
The use of robots in surgery can be dated back to 1985, when a PUMA 560 robotic surgical arm was used to perform a neurosurgical biopsy. Usually robotic surgeries are minimally invasive because they allow the surgeons to perform more precise incisions using minute instruments, thus ensuring better outcomes and faster patient recovery time.
These robots can be effective in many ways;
- They can make deep, precise incisions, and reach areas that traditional tools cannot
- They can perform repetitive tasks without fatigue
- Cognitive robots supported by deep-learning algorithms can observe surgical procedures, analyze current and past data (input by the staff) and recommend ways to improve surgical performance
- For surgeons, surgeries can be physically demanding and a slight hand tremor or a slip can cost dearly. In these cases, robots can be effective in assisting surgeons, thus not only reducing the physical strain on the surgeons, but also helping deliver better outcomes
Today, one of the most prominent surgical robots is the da Vinci surgical system made by US-based Intuitive Surgicals. It can help surgeons perform complex procedures such as hysterectomies, removal of thyroid cancer and more. Aside from this, the other robots have been used for common, low-risk procedures like cholecystectomy and gallbladder removal. While the adoption of robots comes with its risks, data by Research & Markets indicates that owing to a higher geriatric population and increase in chronic diseases, the market for surgical robots is likely to increase and touch $16.77 billion (from $5.46 billion in 2020) by 2031.
AI for Virtual Nursing Assistance
Think of the number of times you’ve tried to self-diagnose by searching the web with your symptoms. Often, the results that throw up would either be as simple as common flu or as risky as a severe complication. In other words, they may not provide an accurate diagnosis. This is where virtual nursing assistants come in. These are chatbots that are available 24/7 to interact with patients and guide them on a course of treatment or medication. For example, if a patient is experiencing some symptoms, he/she can chat with a virtual assistant, which will in turn collect data on symptoms, past history and location, and diagnose, even recommend a doctor if needed.
Virtual assistants have several other use cases too; they can be used by healthcare providers to offer remote assistance, issue follow-ups, schedule appointments, send reminders, help users identify nearest healthcare providers and doctors based on their diagnosis and the like. This technology has the potential to reduce hospital readmissions (thus reducing the workload of healthcare providers), diagnosing diseases early, and lowering cost of medical care, to name a few.
AI for Administrative Tasks
According to The Brookings Institution, AI has the potential to automate 40% of tasks performed by healthcare support staff and 33% of the tasks performed by practitioners. Think about it. With the help of voice-to-text, doctors can prepare charts, order tests and prescribe medications, administrative staff can reduce time spent on phone, in billing and in follow-ups by adopting virtual assistants and the like.
Especially today, when doctors and healthcare staff are overworked, using AI to automate a large portion of repetitive tasks can save providers time, effort and resources.
AI for Patient Intake & Triage
Patient intake and triage is a crucial area where AI can prove to be effective. Often, when patients come into hospitals for care, they spend an enormous amount of time filling out forms. AI can automate this process with the help of chatbots and assistants. They can predict which patients require immediate attention, which doctor they need to be directed to, and whether they need to wait to get specialized care. This can significantly cut down wait times in emergency rooms, and even reduce stress for healthcare staff and doctors.
AI for Medical Imaging
The use of AI in medical imaging is being widely explored and talked about today. Specifically, radiologists and pathologists are exploring the potential for AI to generate imaging information without the need for biopsies and tissue samples, which can be tedious and time-consuming (for analysing the medical images), and also lead to infections. For example, the Radiology Society of America has indicated that AI can observe metabolic brain changes and predict Alzheimer’s years before it sets off. Similarly, in 2020, Google Health began working on an AI-based imaging system that can detect breast cancer quicker than healthcare staff.
Providing End-to-end Care
While we are yet to realize the full potential of AI, from mundane tasks like billing management to performing complex surgical procedures, AI has the ability to bring in process efficiencies, save time and money, and even save lives proactively.
So far, while we saw the impact of AI in global markets, India is not far behind in its adoption and invention of AI technologies, a topic we will explore in the last part of this series on AI in healthcare.
