Inventors: Dr. Amir Glik – Director of the Cognitive Neurology Clinic at Beilinson Hospital
Dr. Chen Hajaj – Faculty member in the Department of Industrial Engineering and Management and Head of the Research Center for Data Science at Ariel University
Dr. Orit Refaeli – Research Fellow, Department of Industrial Engineering and Management, Ariel University
Dr. Anat Goldstein – Faculty member, Department of Industrial Engineering and Management, Ariel UniversityDr.
Alzheimer’s disease is one of the most common diseases in the world among neuro-degenerative diseases. Alzheimer’s is manifested in continuous and irreversible cognitive and functional deterioration. Dementia has a significant economic impact on society; According to a recent report by the American Alzheimer’s Organization, in 2021 there were over 6 million people in the United States with Alzheimer’s or other dementia diseases. The total cost of treating these patients was $ 350 billion (Alzheimer Association, 2021). It is known that 30% of cases of dementia are preventable by balancing vascular risk factors in the years before the onset of the disease.
Assuming that the proposed approach in this project will allow for early detection and prevention of at least 30% of dementia cases then about 2 million patients in the US will receive recommendations from doctors to balance their condition with lifestyles changes that will amongst other things, reduce their cardiovascular risk factors.
Assuming that only 20% of these patients will follow these recommendations then the he total cost of treatment in the U.S. will be reduced by $ 70 billion a year.
Moreover, there are new drugs in the pipeline for the treatment of pre-clinical AD which will necessitate indemnification of at risk populations for developing AD.
The project deals with the establishment of a decision support system for the early identification of subjects at risk of developing Alzheimer’s disease and for measuring the progression of the disease. The system is based on machine learning models using Electronic medical records (EMR) data of Clalit Health Services patients. The database includes personal medical information collected in the community over 20 years.
At this point the model indicates the ability to identify about 80% of the patients who developed Alzheimer’s based on data from the ten years before the diagnosis of the disease.