Mayo Clinic researchers have developed a brand new synthetic intelligence (AI) software that helps clinicians determine mind exercise patterns linked to 9 kinds of dementia, together with Alzheimer’s illness, utilizing a single, broadly obtainable scan—a transformative advance in early, correct analysis.
The software, StateViewer, helped researchers determine the dementia sort in 88% of circumstances, in response to analysis printed on-line on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It additionally enabled clinicians to interpret mind scans practically twice as quick and with as much as thrice larger accuracy than customary workflows. Researchers skilled and examined the AI on greater than 3,600 scans, together with photographs from sufferers with dementia and other people with out cognitive impairment.
This innovation addresses a core problem in dementia care: figuring out the illness early and exactly, even when a number of situations are current. As new remedies emerge, well timed analysis helps match sufferers with essentially the most acceptable care when it could have the best impression. The software may deliver superior diagnostic assist to clinics that lack neurology experience.
The rising toll of dementia
Dementia impacts greater than 55 million individuals worldwide, with practically 10 million new circumstances every year. Alzheimer’s illness, the most typical type, is now the fifth-leading reason behind dying globally. Diagnosing dementia sometimes requires cognitive exams, blood attracts, imaging, scientific interviews and specialist referrals. Even with intensive testing, distinguishing situations similar to Alzheimer’s, Lewy physique dementia and frontotemporal dementia stays difficult, together with for extremely skilled specialists.
StateViewer was developed beneath the path of David Jones, M.D., a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Synthetic Intelligence Program.
“Each affected person who walks into my clinic carries a singular story formed by the mind’s complexity,” Dr. Jones says. “That complexity drew me to neurology and continues to drive my dedication to clearer solutions. StateViewer displays that dedication—a step towards earlier understanding, extra exact remedy and, in the future, altering the course of those ailments.”
To deliver that imaginative and prescient to life, Dr. Jones labored alongside Leland Barnard, Ph.D., a knowledge scientist who leads the AI engineering behind StateViewer.
“As we had been designing StateViewer, we by no means overlooked the truth that behind each information level and mind scan was an individual dealing with a troublesome analysis and pressing questions,” Dr. Barnard says. “Seeing how this software may help physicians with real-time, exact insights and steering highlights the potential of machine studying for scientific medication.”
Turning mind patterns into scientific perception
The software analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which reveals how the mind makes use of glucose for vitality. It then compares the scan to a big database of scans from individuals with confirmed dementia diagnoses and identifies patterns that match particular varieties, or combos, of dementia.
Alzheimer’s sometimes impacts reminiscence and processing areas, Lewy physique dementia entails areas tied to consideration and motion, and frontotemporal dementia alters areas accountable for language and habits. StateViewer shows these patterns via color-coded mind maps that spotlight key areas of mind exercise, giving all clinicians, even these with out neurology coaching, a visible clarification of what the AI sees and the way it helps the analysis.
Mayo Clinic researchers plan to develop the software’s use and can proceed evaluating its efficiency in a wide range of scientific settings.
Extra data: Leland Barnard et al, An FDG-PET–Primarily based Machine Studying Framework to Help Neurologic Resolution-Making in Alzheimer Illness and Associated Problems, Neurology (2025). DOI: 10.1212/WNL.0000000000213831
