The team's paper, "Machine Learning Based Multi-Modal Prediction of Future Decline Toward Alzheimer's Disease: An Empirical Study," published Nov. 16 in PLOS ONE.

Trying to figure out whether someone has Alzheimer's disease usually involves a battery of assessments - interviews, brain imaging, blood and cerebrospinal fluid tests.

About 55 million people worldwide are living with dementia, according to the World Health Organization. The most common form is Alzheimer's disease, an incurable condition that causes brain ...

AI machine learning models for predicting Alzheimer’s were developed using International Classification of Diseases Tenth Revision (ICD-10) codes from electronic health records (EHRs) and ...

UCLA Health researchers have identified four distinct pathways that lead to Alzheimer's disease by analyzing electronic ...

Identifying several predictive factors for scoring the Alzheimer’s Disease risk using machine learning models can prevent recurrence or mitigate their adverse effects.

UCSF scientists found a way to predict Alzheimer’s disease up to seven years before symptoms appear by analyzing patient records with machine learning. Conditions that most influenced prediction of ...

In this interview, Nikita Goel shares her work developing a machine learning approach for predicting Alzheimer’s disease progression.

ALZHEIMER’S disease could be predicted seven years before you develop it by AI, a study suggests. Machine learning models were able to spot early warning signs of the memory-robbing condition ...