When I think of doctors, I will admit that one of the first images that comes to my mind is that of Dr Gregory House. No, not really in terms of bedside manner, but more in terms of his problem-solving skills. For a long time, he impressed me with his dedication, even at the eleventh hour. He could easily find connections between previous cases, go through a patient’s history quickly but also meticulously, tirelessly keep on looking for any abnormalities…Well, Dr House is not a real person. I am not a doctor myself but I can imagine that productively going through a similar kind of problem-solving process day after day (at the beginning of a shift, at the end of long hours) must require an incredible amount of energy, skill and dedication. All while time is of the essence. Hats off to doctors, nurses and all other medical staff. Truly.

What if help could be provided? There are many steps that go from patient admittance to discharge: can any of these steps be facilitated by technology?

Enter computer science. Computer scientists look at a problem, examine the information available, and come up with an algorithm to solve that problem. The faster the method, the more accurate the results, well, the happier computer scientists are. And so, naturally, it was only a matter of time before they would have started working on health data! Health informatics, computational medicine, genomic medicine…these are only a few of the fields associated with this emerging and, quite frankly, thriving intersection of medicine, engineering and computer science. The questions computer scientists are trying to answer are diverse. What next step should be taken in treating a critically ill patient for better outcome? Can mobile technology be used to help contact tracing in the fight against Covid-19? Can we create wearable technology that guides a surgeon while his gloved hand holds a scalpel?

Suddenly, the doctor does not work alone. He collaborates with a team of computational scientists, and is aided by machines and algorithms. The future is here, it is already happening! My view of Dr House as the ideal problem-solver–a person staring into nothingness as he bounces a tennis ball off the walls of his office–is perhaps slightly out-of-date.

But still, there is a long way to go. Can we create algorithms that are not biased against one group of individuals? Can we make sure that any data we have reflects the diversity of the population? These are only some of the questions that need to be addressed.