Within the walls of a 19th-century chapel on the outskirts of Barcelona, a heart starts to slowly contract. This is not a real heart but a virtual copy of one that still pounds inside a patient's chest. With its 100 million patches of simulated cells, the digital twin--a fully functional simulation of human anatomy-- pumps at a leisurely pace as it tests treatments, from drugs to implants. This digital twin pulses within MareNostrum, a supercomputer used by scientists to simulate features of the real world. These simulations can look just like the real thing, but they are vastly more sophisticated than Hollywood visual effects because they behave like the real thing--from how the heart moves to the charged atoms that zip in and out of its cells.

Armed with a mouse and computer screen instead of a scalpel and operating theatre, cardiologist Benjamin Meder carefully places the electrodes of a pacemaker in a beating, digital heart. Using this "digital twin" that mimics the electrical and physical properties of the cells in patient 7497's heart, Meder runs simulations to see if the pacemaker can keep the congestive heart failure sufferer alive, before he has inserted a knife. The digital heart twin developed by Siemens Healthineers is one example of how medical device makers are using artificial intelligence (AI) to help doctors make more precise diagnoses as medicine enters an increasingly personalised age. The challenge for Siemens Healthineers and rivals such as Philips and GE Healthcare is to keep an edge over tech giants from Alphabet's Google to Alibaba that hope to use big data to grab a slice of healthcare spending. With healthcare budgets under increasing pressure, AI tools such as the digital heart twin could save tens of thousands of dollars by predicting outcomes and avoiding unnecessary surgery.

HEIDELBERG, Germany (Reuters) - Armed with a mouse and computer screen instead of a scalpel and operating theater, cardiologist Benjamin Meder carefully places the electrodes of a pacemaker in a beating, digital heart. Using this "digital twin" that mimics the electrical and physical properties of the cells in patient 7497's heart, Meder runs simulations to see if the pacemaker can keep the congestive heart failure sufferer alive - before he has inserted a knife. The digital heart twin developed by Siemens Healthineers is one example of how medical device makers are using artificial intelligence (AI) to help doctors make more precise diagnoses as medicine enters an increasingly personalized age. The challenge for Siemens Healthineers and rivals such as Philips and GE Healthcare is to keep an edge over tech giants from Alphabet's Google to Alibaba that hope to use big data to grab a slice of healthcare spending. With healthcare budgets under increasing pressure, AI tools such as the digital heart twin could save tens of thousands of dollars by predicting outcomes and avoiding unnecessary surgery.

Armed with a mouse and computer screen instead of a scalpel and operating theatre, cardiologist Benjamin Meder carefully places the electrodes of a pacemaker in a beating, digital heart. Using this'digital twin' that mimics the electrical and physical properties of the cells in patient 7497's heart, Meder runs simulations to see if the pacemaker can keep the congestive heart failure sufferer alive - before he has inserted a knife. The digital heart twin developed by Siemens Healthineers is one example of how medical device makers are using artificial intelligence (AI) to help doctors make more precise diagnoses as medicine enters an increasingly personalized age. Siemens Healthineers has built up a vast database of more than 250 million annotated images, reports and operational data on which to train its new algorithms. In the example of the digital twin, the AI system was trained to weave together data about the electrical and physical properties and the structure of a heart into a 3D image.