Sciences The use of artificial intelligence is changing the way hospitals operate
Medical staff examine a woman's breasts for breast cancer using a mammogram. picture
© Hannibal Hanschke/DPA
Artificial intelligence is already changing the way hospitals in Saxony operate today – from optimal surgical planning to early detection of tumors. Patients in particular can benefit from this.
The use of artificial intelligence (AI) is already changing the way we work in hospitals in Saxony. “There is a wide range of processes in healthcare that can be improved through digitalization and artificial intelligence,” says Dario Antwiler, Business Head “Healthcare Analytics” at Fraunhofer IAIS. In hospitals, for example, AI is already being used for optimal surgical planning, writing physician letters, and automated billing coding. This saves time and allows more time to treat patients.
According to Antwiler, the use of artificial intelligence will, among other things, change the treatment of patients in the long term. For example, treatments can be personalized and tailored to the individual needs of patients. However, for health workers to engage more with AI, they must first receive more training.
Detect critical situations in real time
At the University Hospital Leipzig, for example, different systems equipped with artificial intelligence are already being used in different fields. The so-called “traffic light” – a decision support system – helps, for example, to recognize the rare “refeeding syndrome”. This is a complex, potentially life-threatening symptom that can occur in patients with long-term malnutrition when adequate nutritional intake is resumed. Accordingly, more than half of the cases detected by the “traffic signal” are overlooked without the system.
Early detection of tumors
Dresden University Hospital also uses artificial intelligence in different fields. For example, women at increased risk of breast cancer can get earlier diagnosis using AI-powered software. This is also possible for other tumors. Studies have shown, for example, that the AI-based software compares the smallest nodules and calcium clusters, which could be precursors to cancer, with existing data from more than five million images, thus enabling faster diagnosis.
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