Addenbrooke's Hospital in Cambridge along with 20 other hospitals from across the world and healthcare technology leader, NVIDIA, have used artificial intelligence (AI) to predict Covid patients' oxygen needs on a global scale. The research was sparked by the pandemic and set out to build an AI tool to predict how much extra oxygen a Covid-19 patient may need in the first days of hospital care, using data from across four continents. The technique, known as federated learning, used an algorithm to analyse chest x-rays and electronic health data from hospital patients with Covid symptoms. To maintain strict patient confidentiality, the patient data was fully anonymised and an algorithm was sent to each hospital so no data was shared or left its location. Once the algorithm had'learned' from the data, the analysis was brought together to build an AI tool which could predict the oxygen needs of hospital Covid patients anywhere in the world.

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare, that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cellphones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare, that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cellphones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare) that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cell phones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."