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News Center
AI Camera Technology Helps Doctors Quickly Assess Severity of Infections
A significant number of patients who visit healthcare centers are seeking help for symptoms like sore throats, coughs, and fever. While many of these infections are harmless and self-resolving, they can sometimes be the initial signs of more severe and potentially life-threatening illnesses such as pneumonia, COVID-19, and Lemierre’s syndrome. It is crucial to quickly evaluate the severity of these symptoms to provide necessary treatment without the inappropriate use of antibiotics. The overuse of antibiotics leads to the development of resistant bacteria strains, diminishing the effectiveness of these drugs. Currently, the severity of an infection is determined by checking vital signs, which are key indicators of a person's physical health, using a variety of instruments. Now, a new technology that can measure a patient’s pulse, breathing, and blood pressure simply by scanning their face could provide a tool for quickly assessing the severity of acute infection and other medical conditions.
The newly developed method by researchers at the University of Gothenburg (Gothenburg, Sweden) combines camera technology, software, and artificial intelligence (AI) to potentially replicate the results obtained from traditional instruments by simply scanning a patient's face for 30 seconds. In a recent study involving over 200 patients suspected of having COVID-19, this camera-based method was clinically tested and shown to enhance both the assessment of severity and the accuracy of diagnoses. The technology was able to provide data on the patient’s heart rate, oxygen saturation, respiratory rate, and blood pressure. Although the findings are promising, they require further validation, particularly concerning the precision of the measurements.
“The new AI method means that measurements are faster, more convenient for the patient, easier for the healthcare provider, and involve less risk of infections being spread via measuring equipment,” said Stefan Malmberg from the University of Gothenburg. “This type of research is crucial for the development of new healthcare technologies.”
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