Researchers have developed a machine learning algorithm that can accurately detect early signs of Alzheimer’s disease. These signs are visible in specific brain scans but are difficult for doctors to identify. In a pilot project, the AI demonstrated a success rate of 100%. The early detection of Alzheimer’s is still a challenge for even experienced medical professionals. However, Jae-Ho Sohn and his colleagues at the University of California have developed a computer program that can predict Alzheimer’s years in advance based on numerous brain scans, even before the patient shows any symptoms.
Currently, Alzheimer’s and dementia can only be diagnosed reliably once the brain has already begun to deteriorate. Sohn explains that at this stage, the loss of brain tissue is already so severe that interventions are often too late. To address this issue, Sohn and his team developed an AI that can accurately detect Alzheimer’s many years in advance. They trained the software with thousands of PET scans of Alzheimer’s patients in the early stages and then tested it on previously unseen brain scans. The results were surprising, with the AI achieving a 100% success rate in identifying cases that later turned out to be Alzheimer’s.
While the AI’s Alzheimer’s detection is still in the pilot stage and requires further evaluation and improvement, the researchers are optimistic that it will one day be used for early diagnosis. Early detection is crucial because it gives medical professionals the opportunity to slow down or even halt the progression of the disease. The success of this project highlights the potential of AI in healthcare and the importance of continued research in this field.
