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Scientists have developed a "digital mask" that will permit the storage of facial photographs in medical records while limiting the extraction and sharing of potentially sensitive personal biometric data. Researchers from the University of Cambridge and Sun Yat-sen University in Guangzhou, China, used three-dimensional (3D) reconstruction and deep learning algorithms to remove recognizable features from facial images while keeping disease-relevant features required for diagnosis in research published today in Nature Medicine. Images of the face can be helpful in spotting illness symptoms. Deep forehead wrinkles and wrinkles around the eyes, for instance, are strongly linked to coronary heart disease, whereas aberrant alterations in eye movement may be an indication of poor visual function or developmental issues with the visual-cognitive system. Facial photos invariably capture additional biometric data about the patient, such as their race, sex, age, and mood. Data leaks are...

Researchers at the Mayo Clinic have discovered that analyzing patterns of changes in laboring women using artificial intelligence (AI) algorithms can assist predict if a vaginal delivery will be successful and result in a healthy mother and child. The research results were released in PLOS ONE. Abimbola Famuyide, M.D., a Mayo Clinic OB-GYN and senior author of the study, says, "This is the first step to applying algorithms in providing effective guidance to physicians and midwives as they make key decisions during the birthing process." "We anticipate that the algorithm will operate in real time, updating the risk of a negative outcome with each new piece of information entered during an expectant woman's labor once it has been verified by additional research. This could lower the number of cesarean deliveries as well as complications for both mothers and newborns." Women who are in labor are aware of the value of routine cervical exams to monitor the progressio...