‘A Lot Of Promise’: DeepMind Algorithm Detects Serious Kidney Condition In Minutes, But Miss Rate Is High
Acute kidney injury is caused by serious health conditions, including sepsis, and affects one in five people admitted to hospital. Quick diagnosis can save lives. While the machine learning system can reduce the time between when the condition is diagnosed and treatment begins within hours, researchers say it was far from perfect and more testing needs to be done.
Stat:
DeepMind AI Predicts Loss Of Kidney Function Two Days In Advance
One of the biggest challenges hospitals face is predicting when frail patients will decline into a life-threatening spiral. Subtle changes in health status get lost in a sea of data that is too vast for humans to effectively monitor. In a paper published Wednesday in the journal Nature, researchers at DeepMind describe a possible solution: A machine learning system capable of crunching hundreds of thousands of data points in electronic health records to alert physicians to an impending crisis long before it happens. (Ross, 7/31)
The Wall Street Journal:
Google Algorithm Aims To Identify At-Risk Kidney Injury Patients
Google’s artificial-intelligence unit says it has developed an algorithm that can predict who is at high risk of developing a common kidney condition. The algorithm, developed by the DeepMind Health laboratories at Google parent company Alphabet Inc., marks a new application of machine learning in health care. Yet it also shows the shortcomings of many such efforts so far, in this case partly because the algorithm is accurate a little more than half the time. (Olson and Abbott, 7/31)
BBC News:
Kidney Condition Detected In Minutes By App
The condition is more common in older patients and, if not treated quickly, can affect other organs. It accounts for around 100,000 deaths every year in the UK. During a trial at London's Royal Free Hospital, doctors and nurses received warning signals via a mobile phone app in an average of 14 minutes, when patients' blood tests indicated the condition. (Pym, 7/31)
