Artificial Intelligence in Alzheimer’s Prediction: What to Know?
Artificial Intelligence is a machine or software that is designed and programmed in a way so that it can work and think like a human. From a PCs to personal assistants like Siri to surveillance systems, AI is already involved deeply in our life.
This technology has emerged as a ray of hope for Alzheimer’s patients as well as healthcare professionals. It is predicted to diagnose the symptoms of Alzheimer’s six years before traditional diagnoses.
How AI Can Detect Alzheimer’s?
Artificial Intelligence can predict Alzheimer’s earlier, making it easier for physicians to take timely steps in preventing disease progression during its early stages. Here’s how researchers at the University of California, San Francisco have used AI to detect Alzheimer’s:
First of all, they developed a special learning algorithm on a special imaging technology called 18-F-fluorodeoxyglucose positron emission tomography (FDG-PET). In this scanning technology, a radioactive glucose compound is injected into the blood. PET scans keep the track of FDG uptake in the brain cells. This way, they act as an indicator of metabolic activity.
A team of researchers sourced data from the Alzheimer’s disease Neuroimaging Initiative. The data set has over 21,00 FDG PET brain scan from nearly 1,000 patients.
Researchers trained the deep learning algorithm on the results of 90 percent of the dataset and then tested it on the remaining 10 percent of the dataset. Through deep learning, the algorithm was able to teach itself metabolic patterns that corresponded to Alzheimer’s disease.
The algorithm was conducted on the set of 40 imaging scans that it had never processed. It achieved total sensitivity at detecting the disease an average of more than six years before the final diagnosis.
Speaking on the importance of early diagnosis, Jae Ho Sohn, MD, MS and resident physician at the university’s radiology department, states:
“One of the difficulties with Alzheimer’s disease is that by the time all the clinical symptoms manifest and we can make a definitive diagnosis, too many neurons have died, making it essentially irreversible,”
Dr. Mallar Chakravarty, a computational neuroscientist at McGill University’s Douglas Mental Health University Institute, has created an AI system to determine if a patient is likely to develop Alzheimer’s five years before any key signs occur. The algorithm includes genetic makeup, blood test results and MRI scans of the patients to learn the possibility of the disease. The aim is to identify patients who are more vulnerable to Alzheimer’s.
However, Dr. Chakravarty also admits the limitations of the algorithm in these words:
“These algorithms will only learn what we tell them to learn, so they’re only as good as the problem that we teach them to solve. It won’t learn anything more or anything less. In our case, in terms of health care data, you’re somewhat limited by where the data comes from and how much data you have access to. One major limitation is that different clinicians or sites have various names for the same thing, so how do you standardize that across sites to train your algorithm? I think that is going to be a really important thing to overcome in the future.”
If Alzheimer’s is Detected on Time
It is clear that AI for Alzheimer’s detection is really a groundbreaking innovation. It can help a patient get a timely diagnosis which, in turn, can prevent complications, rapidly appearing symptoms symptoms and healthcare costs.