Alzheimer’s disease often starts its work long before anyone notices a problem. That gap, sometimes stretching a decade or more before memory symptoms appear, is where a research team centered at MIT says it wants to intervene. The group has released FINGERS-7B, which it describes as the first AI foundation model built specifically to help make Alzheimer’s preventable by identifying people at risk earlier and more accurately. The model, developed by a team of AI researchers, physicians, and scientists, combines lifestyle, clinical, genomic, and proteomic data from tens of thousands of at-risk individuals. By reading those signals together, rather than one at a time, the system is designed to uncover what the team calls multi-omic biomarkers for preclinical Alzheimer’s disease. Looking across many kinds of biological evidence What makes the project unusual is not just the scale of the data, but the way the model handles it. FINGERS-7B was trained to learn jointly from lifestyle information, clinical records, biomarkers, genomic data, and proteomic signals. The broader platform around it is called FINGERPRINT, which pairs the …