Using Artificial Intelligence in Healthcare is one such subject. If you have to believe what the media says, AI is going to transform healthcare in the near future. In fact, the services of the doctor may not be needed very often, if at all. AI will do everything in medicine including diagnosis, treatment and even finding out new drugs.
But not everyone is so optimistic or even welcoming. The idea of machines taking care of our health is creepy to some. Others claim that AI can never replace a doctor, at least not in a foreseeable future. Medicine is too complex for machines to figure out.
(You must have noted that I am using Healthcare and Medicine interchangeably. The reason being that this is what most people do. Healthcare is the practice of medicine and as such is wider than it. I refer to healthcare as including medicine.)
The reality, like in the case of GST and most other things, will be somewhere in the middle. The purpose of this article is to find that balanced view. In effect, what I will be saying is:
“while the replacement of the doctor is a faraway dream, there are a number of things that AI can do in medicine even today. This can turn out to be valuable help for doctors, patients and other stakeholders”.
Let me first present a short introduction to AI.
AI, like Philosophy, is a very hard term to define. AI is not really one technology. It is a collection of techniques. Strictly speaking, AI is actually an ambition. The ambition of machines to imitate human capabilities.
But this definition does not take us very far. Since human capabilities are many, ranging from walking to writing poems, imitating any of these capabilities can be called AI. So for our purposes, we will define AI as the pursuit of those capabilities that are strong points of human beings.
As an example, consider language. Reading an article and understanding its gist is a simple matter for us humans. For machines to achieve this capability will be quite something. If that happens, machines can go through a number of articles for us and feed us with the just the little bits that we need.
A whole lot of mathematical and computational techniques have been developed by researchers in the last sixty years to achieve this goal. Deep Learning, Machine Learning and NLP are some names given to a bunch of such techniques. In the last few years, AI has risen to prominence mainly due to three reasons – availability of data, increase in computing power and discovery of new methods.
Armed with that introduction, let’s try and put down the areas where AI can make a difference in healthcare. While we do that, we can also try to answer the ‘replace the doctor’ question.
Diagnosis: Diagnosis is the hardest part of medicine. There is no definite pathway to diagnosing a patient. A lot depends on the experience and intuition of the doctor, in that way, it is more of an art than science. As of now, it is difficult to see AI taking over this role. However, there are many areas where AI is already making a difference:
- Conditions in which diagnosis is dependent on analysis of a signal over time, such as an ecg or an eeg. Machine Learning combined with signal processing can achieve good results here. Arrhythmia or irregular heartbeat is an example of such a condition that AI can detect well.
- Diagnosing some disorders involves referring to a lot of data such as past and present reports, images and history. Gatro-intestinal disorders are notoriously difficult to diagnose and require a lot of information to refer. AI can make a big difference here by sifting through the pile of data and presenting important facts to the doctor.
- In radiology, the volume of cases is huge and the radiologist needs to look at every image to come to a conclusion. Some investigations like MRI produce a large number of images for each patient. This makes the doctor’s time a bottleneck in handling the ever growing number of patients. Deep Learning has shown great promise in being able to classify medical images. For example, it can separate images that indicate normal functioning from those that have some abnormality. This will enable the radiologist to focus on the abnormal cases first. This method will also be a boon for the remote places where a radiologist is not available.
- AI has provided a new method for laboratory investigations. This may mean that in the future most lab tests including pathology will be done with basic instruments at a very low cost. In a disease like HIV/AIDS, being able to determine the viral load in a quick and inexpensive way can be a very big benefit to the patients.
Treatment: The biggest contribution AI can make to treatment of patient is in the area of drug discovery. Currently, discovering a new drug costs more than 2.5 billion dollars and takes more than a decade. The pharmaceutical industry is desperately searching for new ways to reduce the cost and time. AI may be one of the solutions to this problem. Machine Learning and Deep Learning are being used in various stages of drug discovery, such as identifying candidate molecules and studying the expected response of the new drug.
In our fight with cancer, AI may be an important weapon. Personalized Oncology is rapidly getting attention from the medical community as the way forward in battling with the cancer scourge. To describe in brief, cancer is not one disease – the cancer of every patient is different. If the individuality of cancer is decoded, a personal treatment path can be planned for every patient. AI will become a key part of this process.
AI is already playing a role in treatment by making robots that perform surgeries. This contribution will grow in the time to come with the robot costs falling and capabilities growing. This will reduce the strain on surgeons and they will be able to perform far more surgeries in the same time.
Care: Care during the illness and recovery is as important as the right diagnosis and treatment. Along with IoT, AI will transform patient care. Everything from medicine intake to prescribed activity will be monitored by these systems. Monitoring includes two components – sensing and analysis. While the sensing part is done by the IoT devices, analysis is provided by AI.
Prevention: Prevention is definitely preferred to hospitalization and AI is going to play a major role in this. It will involve both personal and public health. Personal health is monitored by the wearables and other simple devices. The AI systems will process this data to look for possible indications of disorders so that they can be fixed inexpensively.
Public health will be monitored in the same way but from data that is coming from various healthcare institutes. This enormous data will forewarn us about various health risks such as outbreaks of diseases. It will enable the state to take measures to avoid the calamities.
In short:
To summarize, AI will really be a transformational technology for healthcare. It will make healthcare cheaper and faster and enable it to reach more number of people. AI will reduce the strain on doctors and nurses. However, for the future that we can see, AI will serve more as an assistant to the doctors, rather than being their replacement.
Devesh Rajadhyax
