After last year’s blog post looking at the basics of artificial intelligence (AI) and its potential within healthcare, we’ve delved one step further to see what’s been happening in the past few months and what could be happening over the next few years.
NHSX and government pledges
Set up last year, NHSX brings together world-leading tech, digital, cyber and data experts to transform the NHS into the world’s most advanced healthcare system.
As part of this, a new dedicated AI lab is set to be launched in April 2020. Backed by £250 million, the project will consider how AI can be used to the benefit of patients; whether that’s the deployment of existing AI methods, the development of new technologies or the testing of their safety.
Alongside this the government recently announced its ‘AI and Data Mission’, as part of the Industrial Strategy’s Grand Challenges. This aims to put the UK at the forefront of the use of AI and data in early cancer diagnosis and treatment, with estimates predicting that over 50,000 more patients could see their cancer detected at an early stage. This would mean around 20,000 fewer people dying within five years of their diagnosis compared to today.
Similar benefits could be seen for those with brain tumours, with a recent study by The Brain Tumour Charity showing that AI is quicker and more accurate in identifying brain tumour tissue than pathologists.
Both of these crucial interventions would inevitably have a positive effect in other areas, enabling money to be saved that would have been spent on further treatment. Such breakthroughs could also help reduce the workload on NHS staff, something that’s particularly important at a time of increased pressures.
Reinforcing the NHS’ attitude towards AI, Secretary of State for Health and Social Care, Matt Hancock has continued his backing, telling BBC News: “The power of artificial intelligence to improve medicine, to save lives, to improve the way treatments are done, that power is enormous. In this country, we’ve got the opportunity to be one of the leading countries in the world at using this new technology.
“I want the NHS, through its AI lab, to actually be searching itself for new insights that are going to save lives.”
The NHS has also established a £140 million AI Award to help accelerate the testing and evaluation of the most promising AI technologies. The award will support technologies across the spectrum of development; from initial feasibility to evaluation within the NHS.
Providing insight and patient care suggestions
Much has been made of patient data privacy in relation to AI, and that’s something which clearly needs to be addressed before software is developed, progressed and approved.
As well as absorbing AI company DeepMind, Google has entered a US-based cloud computing partnership with Ascension Health. Despite confidentiality and advertising concerns, this partnership has powerful potential to integrate and process data, which can then give healthcare providers new insights and suggestions for patient care.
Whilst it’s unlikely we’ll see a similar partnership rolled out in the UK, its workings and results will be something of keen interest to the NHS and healthcare stakeholders.
Leading the fight against antibiotic resistance
Antimicrobial resistance (AMR) is one of the biggest ongoing threats to global health, but Abtrace are leading the fight through AI against the overuse of antibiotics. With 30% of all such prescriptions inappropriate, Abtrace’s AI platform helps NHS clinicians prescribe the most appropriate antibiotic for each individual patient.
The platform processes a patient’s healthcare notes through an augmented decision-making tool. Its algorithm contains millions of data points on dosages and success rates in treating different infections with different antibiotics, against which the patients’ notes are then compared. In a matter of seconds, the tool presents a recommendation for whether or not an antibiotic should be prescribed, and which antibiotic would be appropriate if so.
This helps guide doctors to the right decision, with the risk of antimicrobial resistance significantly reduced. The tool also has the added bonus of increasing efficiency and reducing wasted resources on inappropriate medication.
Predicting the chances of death, heart attack and stroke
At the start of the year, AI was used for the first time to instantly and accurately measure blood flow, helping to predict the chances of death, heart attacks and strokes.
In a study part-funded by the British Heart Foundation and led by University College London and Barts Health NHS Trust, researchers took routine cardiovascular magnetic resonance scans from more than 1000 patients and used AI to analyse the images.
By doing this, the teams were able to precisely quantify the blood flow to the heart muscle and deliver the measurements to the medical teams treating the patients. The results were found to be able to predict chances of death, heart attack and stroke, which can be used by doctors to help recommend treatments to improve a patient’s blood flow.
Helping tackle self-harm content online
The impact of AI isn’t just restricted to healthcare, it’s also been used within social care to help reduce the threat of self-harm content to young people online.
Every year YouTube sees 1.35 million searches for self-harm videos from English speakers, but thanks to an award-winning partnership between Cambridge University academics, social media companies and children’s charities, that threat is being reduced.
CAM.AI is a simple but effective chatbot that engages internet users when they encounter content related to self-harm. The tool attempts to draw the user away and offers support based on recognised cognitive behavioural therapy techniques.
Big possibilities but big questions remain
These are just a handful of the innovative AI healthcare tools in use, with many more exciting projects in the early stages of planning and development.
The use of AI inevitably comes with some complicated challenges — health data is incredibly personal and people are naturally sceptical about trusting the diagnosis decision of a machine.
But while the key sticking points around data quality, privacy and algorithms remain, it’s expected that the level of investment will only increase as more AI technology is deployed and a broader base of test cases is established.
Pete Durlach, Senior Vice President for Healthcare Strategy and New Business Development at Nuance told Healthcare IT News: “With healthy clinical evidence, we’ll see AI become more mainstream in various clinical settings, creating a positive feedback loop of more evidence-based research and use in the field.
“Soon, it will be hard to imagine a doctor’s visit, or a hospital stay that doesn’t incorporate AI in numerous ways.”
The biggest immediate possibilities are around personalised healthcare, particularly around cancer screening and treatments, eye disease and other conditions. But it’s important to remember it’s not just patients who will benefit — clinicians will be in a better position to make the best use of their expertise, helping to inform decisions, save time and increase efficiencies.