Medicine has never been subject to such massive changes as it is now in terms of technological advances and the rise of digital health innovation. It’s important to be aware of these developments because they have implications for the way that Doctors work, how patients look after themselves and how diseases are dealt with by the health service.
Let’s take a look at some examples so that you can start to be familiar and understand these changes. This may be especially helpful for medical school interviews and MMI circuits where such questions may be posed as ‘What do you think are the advantages and disadvantages of artificial intelligence in medicine?’
Be careful what you mean here by ‘AI’ as this is a misused term. An algorithm which suggests that you want to watch The OA on Netflix based on your viewing history is not AI, nor is a rule engine that can tell you that you have a 12% risk of a heart attack happening in the next 5 years. AI is the simulation of human intelligence by computer systems. This includes learning, reasoning and self-correction. Narrow AI is something trained for a particular task, such as Siri on the iPhone. General AI had more extensive cognitive abilities. When presented with an unfamiliar task, a strong general AI system is able to find a solution without human intervention.
AI presents strong possibilities in the field of medicine, over and above cognitive computing. An example would be a computer programme that is able to analyse and act on thousands of blood results simultaneously and identify patients with acute kidney injury such as DeepMind’s ‘Streams’ application. Kheiron Technologies have developed an image analysis AI for detecting cancerous cells in breast biopsy pathology slides, which works as well if not better in some circumstances than Consultant Pathologists.
Babylon Health have a symptom checker AI in their smartphone app which can assist with medical diagnosis and treatment plans. It automates much of the information gathering but don’t worry Doctors are redundant just yet. One of the underlying problems that has been identified with such systems is the presence of potential bias in the underlying machine learning algorithms in AI systems. After all, humans write the code and the decision-making trees underlying AI. Humans are biased, contradictory and make value judgments all the time. It would be a shame if all the AI oriented systems of the future were based on the unworldly preferences of young, white computer geeks who live at home with their parents.
So in summary, health tech is here and it is growing. There are good connotations and bad. There is the possibility that through automation and data processing we can pick up and treat medical problems even more efficiently than ever. However there is the downside that Skynet will take over and that Doctors become technically proficient computers who forget how to treat the human condition. Or is the reality likely to be somewhere in the grey area in between?
We hope that this was a helpful overview of this hot topic in healthcare and you feel more confident tackling it if it comes up as an interview question. Don't hesitate to send us any questions or comments by email at hello@theMSAG.com. Good luck in your interview!
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As part of your medical school interview, be it a panel or multiple mini interview (MMI) circuits, it is likely that you will be asked questions about current issues affecting the healthcare services. Measuring A&E waiting times is a common tool for assessing how well a hospital is performing. It is a good indicator of whether they are correctly staffed and is one of the most common ways which patients experience the health service.