The future of robots in healthcare

With AI revolutionising so many aspects of our life for the better, here are just some of the ways in which innovators are bringing robotics into the world of healthcare.

According to a survey by Gartner, AI bots will power 85% of all customer service interactions by the year 2020.

While robotic financial assistants, legal assistants, and customer contact centres are all going from strength to strength, what about the most person-centric industry of all - healthcare?

The healthcare industry has long taken advantage of cutting-edge technological advances, improving quality of life through ground-breaking treatments and digitised processes.

However, in order for AI to succeed in healthcare, it needs to be developed with patient-centricity in mind. Many patients already struggle with the impersonal aspects of their healthcare provision, so we need robots to enhance their experience rather than add to their feelings of isolation.

With AI revolutionising so many aspects of our life for the better, here are just some of the ways in which innovators are bringing robotics into the world of healthcare.

Treatment plans

One way in which artificial intelligence can improve the patient experience from the ground up is by working behind the scenes.

A recent AI advance by IBM Watson has advanced abilities in recognising and analysing structured and unstructured data found in clinical notes and reports, combining these unique attributes with clinical data and research to identify potential treatment plans to fit each patient.

This approach allows treatment plans to be collated far more quickly than they currently are, and lets the doctors who would otherwise be analysing this data spend more time on the patient-centric aspects of their jobs.

Furthermore, the highly analytical nature of the AI’s treatment options means that patients will be given a truly personalised plan, with attention given to particularities that human analysis may overlook.

Cognitive assistance

Taking AI assistants one step further, IBM’s Medical Sieve project aims to assist radiographers and cardiographers with clinical decision making. With analytical reasoning capabilities and a vast range of clinical knowledge, this cognitive assistant can analyze data from radiology images to detect anomalies and suggest diagnoses.

In the future, all but the most complex of cases will be analysed by cognitive assistants, with physicians overseeing the end results. Again, this will allow doctors’ expertise to be used more efficiently, cutting costs and ensuring that diagnoses are given sooner.

While previous attempts at diagnostic computer systems have been based using predefined and specific assumptions, resulting in poor quality diagnostic performance, AI systems allow cognitive assistants to make rational links between facts, increasing their knowledge base as they work, and therefore handling a wider spectrum of diseases.

Diagnostic consultations

One of patients’ biggest concerns about discussing symptoms with a physician is the amount of time the process takes. It can take two days to a week to get an appointment with a GP, and up to a week longer to hear results of any tests taken.

A new app from Babylon is in the process of changing this, with a medical consultation app that can offer diagnoses and appropriate suggestions to patients with minor complaints.

The bot takes into account a user’s personal medical records, as well as drawing from a vast network of clinical knowledge, to check reported symptoms off against a database. The bot can then analyse results to suggest a course of action such as buying over-the-counter medication, treating the condition at home, or contacting a medical professional with the diagnosis.

While only in its early stages, this solution may significantly improve the efficiency of diagnosing minor conditions, allowing doctors to focus on more serious cases. Furthermore, with time and refinement, the bot may be developed to identify a range of more serious conditions.

Virtual nursing

While a robot may be the last thing you think of when it comes to effective home nursing, AI-powered solutions can help patients to feel more independent while accurately monitoring their conditions.

A prototype solution from start-up reminds patients to take their medication, as well as assisting them in monitoring their own condition and follow-up care. Particularly in the case of chronic diseases, this advance could help patients to take control of their own care, living independently at home without the fuss of regular appointments.

Drug development

While AI can be instrumental in the future diagnosis and follow-up stages of an illness, how can robots assist us in developing effective drugs?

The clinical trial process is a lengthy one, and developing the ideal treatment via multiple rounds of trials can take over a decade, at a cost of billions of dollars. Using AI to speed up the process would get vital drugs on the market sooner, providing life-enhancing treatments to those who need it most.

That’s why advances such as Atomwise could revolutionise the pharmaceutical industry, using supercomputers to analyse and recommend potential therapies from a database of molecular structures.

The program has been tested with a search for an existing medicine that could be reconstructed as a viable treatment for ebola. The AI technology discovered two drugs that could significantly reduce infectivity in under one day.

If this technology can be found to meet regulations, timescales for the earliest stages of research can be minimised, and more resources can be put into getting safe, effective AI-selected drugs on the market.

The future

While healthcare will never stop needing a skilled human touch, there is a significant gap in the industry that AI can fill. AI systems are designed to analyse vast quantities of information to make informed judgements within minutes - something that would take days or weeks of a human physician’s time.

Giving such tasks to approved and regulated bots will not only save time and resources, getting treatments to those who need them as quickly as possible. It will also allow doctors and researchers to focus on the patient-centric aspects of their roles, safe in the knowledge that AI is crunching numbers behind the scenes.

What do you think is the most promising application for robotics in healthcare? Join the debate over on LinkedIn or learn about our technologies.