Artificial Intelligence in Medicine
Developments in automation and artificial intelligence are set to revolutionise the workplace - in May 2017, McKinsey estimated that 50% of activities currently carried out by workers have the potential to be automated. Many of us are wondering how our fields may be impacted by this societal shift.
Artificial intelligence in medicine and healthcare has been a particularly hot topic in recent years. While there is a sense of great potential in the application of AI in medicine, there are also concerns around the loss of the ‘human touch’ in such an essential and people-focused profession.
Read on to find out more about how AI is being used in medicine today, how it may be used in the future and what this means for the future of medical professionals.
AI in medicine refers to the use of artificial intelligence technology / automated processes in the diagnosis and treatment of patients who require care. Whilst diagnosis and treatment may seem like simple steps, there are many other background processes that must take place in order for a patient to be properly taken care of, for example:
Gathering of data through patient interviews and tests
Processing and analysing results
Using multiple sources of data to come to an accurate diagnosis
Determining an appropriate treatment method (often presenting options)
Preparing and administering the chosen treatment method
Aftercare, follow-up appointments etc.
The argument for increased use of AI in medicine is that quite a lot of the above could be automated - automation often means tasks are completed more quickly, and it also frees up a medical professional’s time when they could be performing other duties, ones that cannot be automated, and so are seen as a more valuable use of human resources.
According to a study from 2016, physicians spend much more time on data entry and desk work than they do actually talking to and engaging with patients. This revealed, said AMA Immediate Past President Steven Stack, “what many physicians are feeling—data entry and administrative tasks are cutting into the doctor-patient time that is central to medicine and a primary reason many of us became physicians.”
The push, therefore, is not to excessively over-automate the medical and health care fields, but to deliberately and sensibly identify those areas where automation could free up time and effort. The goal is a balance between the effective use of technology and AI and the human strengths and judgement of trained medical professionals.
There is already an incredible amount of technology and automation in play in medicine, whether we realise it or not - medical records are digitised, appointments can be scheduled online, patients can check in to health centres or clinics using their phones or computers. As technology usage has increased in all areas of life, so too has it quietly changed the ways in which we seek medical care.
For example, Futurism lists the following examples of AI already being used in medicine today:
Decision support systems - When given a set of symptoms, DXplain comes up with a list of possible diagnoses
Laboratory information systems - Germwatcher is designed to detect, track and investigate infections in hospitalised patients
Robotic surgical systems - The da Vinci robotic surgical system, with robotic arms, precise movement and magnetised vision, allows doctors to precision surgery that wouldn’t be possible with an entirely manual approach
Therapy - AI Therapy is an online course for people struggling with social anxiety
Reducing human error - Babylon is an online application where patients in the UK can book appointments and routine tests, plus consult with a doctor online, check for symptoms, get advice, monitor their health and order test kits
The potential for increased AI usage in medicine is not just in a reduction of manual tasks and the freeing up of physician’s time, increasing efficiency and productivity - it also presents the opportunity for us to move towards more ‘precision medicine’.
As summed up by Bertalan Meskó (MD, PhD) in an article for LinkedIn, “Artificial narrow intelligence will most likely help healthcare move from traditional, ‘one-size-fits-all’ medical solutions towards targeted treatments, personalised therapies,and uniquely composed drugs.”
For many years, by necessity general practice in medicine has been to gather data and make generalisations. As Meskó puts it, treatment is often based on ‘the needs of the statistical average person’. Now as we are in an age where masses of data can be collected and analysed very quickly, personalising treatment based on specific knowledge is becoming more feasible.
Demonstrating this shift, last year Google released an open source version of DeepVariant, an AI tool for precision medicine. Healthcare IT News also note that alongside Google, rivals IBM and Microsoft are moving into the healthcare IT space with speculation that Apple and Amazon will soon do the same. <
As more studies are published and discussions had around the future of AI and automation, distinct sides to the argument do emerge, particularly when it comes to something like medicine. The general consensus is that while routine tasks and data collection/entry can and perhaps should be taken on by machines, there will always be a need for the human element of the doctor’s role, in things technology cannot provide - judgement, creativity, and empathy, for example. >
This was disputed however in 2016 by Richard and Daniel Susskind, who argued in an article for HBR that, within decades, traditional professions including medicine will be dismantled, “leaving most, but not all, professionals to be replaced by less-expert people, new types of expert, and high-performing systems.”
Even the Susskind’s research, however, doesn’t suggest that the role of ‘doctor’ will completely disappear - more that it will change. Writing for Stat News, Jack Stockert points out that whilst the use of AI on its own may increase efficiency, pairing with AI also improves human performance. He states, “this hybrid model of humans and machines working together presents a scalable automation paradigm for medicine, one that creates new tasks and roles for essential medical and technology professionals, increasing the capabilities of the entire field as we move forward.”
In conclusion, then, whilst it’s unlikely that machines will replace or eradicate the need for human doctors any time soon, those already in or considering a medical profession should be willing to adapt, learn and grow alongside technological advancements. Bryan Vartabedian, again writing for Stat News, sums it up: “I think my profession is headed to evolution, not extinction.”