Scientists from Imperial College Londonhave created an artificial intelligence system that could help treat patients with sepsis. In the study, researchers looked back at US patient records from 130 intensive care units over a 15 year period to explore whether the AI system’s recommendations might have been able to improve patient outcomes, compared with standard care.
The system analysed the medical records of 96,000 US patients with sepsis in intensive care units. Using a process called reinforcement learning – where robots learn how to make decisions and solve a problem – the system, called AI Clinician, went through each patient’s case and worked out the best strategy of keeping a patient alive. The system calculated 48 variables including age, vital signs and pre-existing conditions. The system then predicted the best treatment strategy for each patient with sepsis. The findings showed the AI system made more reliable treatment decisions than human doctors. The team behind the technology say the tool could be used alongside medical professionals, to help doctors decide the best treatment strategy for patients. The results revealed that 98 per cent of the time, the AI system matched or was better than the human doctors’ decision.
Dr Aldo Faisal, senior author from the Department of Bioengineering and the Department of Computing at Imperial, said: “Sepsis is one of the biggest killers in the UK – and claims six million lives worldwide – so we desperately need new tools at our disposal to help patients. At Imperial, we believe that AI for Healthcare is the solution. Our new AI system was able to analyse a patient’s data – such as blood pressure and heart rate – and decide the best treatment strategy. We found that when the doctor’s treatment decision matched what the AI system recommended, they had a better chance of survival.”
The AI Clinician
Professor Anthony Gordon, senior author from the Department of Surgery & Cancer at Imperial explained: “We know that most patients with sepsis need fluid drips and in more severe cases also need vasopressors to maintain blood pressure and blood flow. There is still much debate amongst clinicians about how much fluid to give and when to start vasopressors. There are clinical guidelines but they provide general advice. The AI Clinician is able to learn what is the best option for each individual patient at that moment in time.”
The study also found that mortality was lowest in patients where the human doctor’s doses of fluids and vasopressor matched the AI system’s suggestion. However, when the doctor’s decision differed from the AI system, a patient had a reduced chance of survival. The team found when the doctor’s decision varied from the AI Clinician’s suggestion, it was on average to administer too much fluid and too little vasopressor but importantly it varied between individual patients.
The team say the findings show the AI Clinician could help doctors decide the best treatment strategy for patients. Professor Gordon explained “The AI Clinician was able to ‘learn’ from far more patients than any doctor could see in a lifetime. It has learnt from 100,000 patients and ‘remembered’ them all equally whereas doctors are always susceptible to recall bias, where they particularly remember recent cases or unusual cases”.
Dr Faisal said: “The explosion in artificial intelligence applications in healthcare is currently focused on mimicking the perceptual ability of human doctors, e.g. recognising a tumour from a brain scan as used in diagnostics. However, doctors do more than just diagnose, they treat people. Our AI Clinician system focuses on capturing this cognitive capacity of doctors: Imagine having a doctor watching over you every second of every day, administering a course of treatment, observing how you respond to the treatment, and then adjusting the treatment as your condition evolves.”
Source: Imperial College London