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Facial recognition technology in the healthcare industry is gaining momentum. How is it being applied and what problems is it solving?
Facial recognition technology has been around for some time now. In addition to the public safety and financial services industry, healthcare is another industry that holds a lot of promise for the technology.
According to James Forbis with 4BIS.COM in Cincinnati, OH, In recent years, we have seen significant investments in technology to digitize the healthcare industry. However, it has only been in recent times that we have seen increasing momentum in facial recognition technology, partially driven by improvements in artificial intelligence and ever-growing databases of facial profiles. AI-powered facial recognition systems have allowed healthcare professionals to consider uses of the technology beyond security purposes.
Just what is facial recognition technology, and what are some applications in the healthcare industry? Facial recognition technology is a method of identifying an individual based on their facial characteristics such as skin texture and bone structure. An algorithm assigns numerical values to facial features and compares those values to an extensive database to output a result. Applications in the healthcare industry include not only perimeter security, but also hospital traffic pattern analysis, patient fraud prevention, hospital traffic analysis, and sentiment analysis.
Perimeter security
Public safety and security have long been one of the best applications of facial recognition technology. It is also one of the most important. Law enforcement is using facial recognition technology to scan anyone entering a medical facility to identify individuals who might be a danger to patients, staff, and public safety. Threats can include drug seekers, criminals such as domestic violence and child abuse suspects, and terrorists.
In light of recent public health outbreaks such as the Wujan Coronavirus, AI-based facial recognition technology can be used as the basis of a tool to scan large groups of people to seek carriers of the disease. Rather than seeking out specific individuals, the software could be trained to find and identify people exhibiting particular symptoms such as a fever or other medical or behavioral conditions.
Hospital traffic pattern analysis
Medical facilities can use facial-recognition software to detect patterns about patient and visitor statistics based on gender, age, and other characteristics. With regard to care, medical providers can track individuals without tracking devices such as a patient within a nursing home, assisted living, or outpatient facility.
Patient fraud prevention
Facial recognition technology can help healthcare providers identify individuals posing as patients to access treatments and medications.
Sentiment analysis and diagnosis
Emotion detection is another emerging application of facial recognition technology. It can be used to track several emotions a patient may exhibit during their stay within a facility. Such a system creates data points to monitor a patient’s response to treatment and care. For example, identify when they need more attention when they exhibit pain, sadness, or other emotion.
Facial recognition technology is also being used in the diagnosis of medical conditions. Face2Gene is an application that is being used by clinicians to diagnose rare conditions like Cornelia de Lange syndrome, where patients have rare facial characteristics that may have been overlooked by the physician because they did not know what to look for.
As technologies mature and become, increasingly sophisticated and complex, difficult ethical, legal, and privacy-related questions must be answered surrounding their use. This is particularly important pertaining to the use of AI-based facial recognition technologies in healthcare and public health as they have the potential of infringing upon an individual’s civil liberties and right to privacy.
