How IBM Is Employing AI To Predict Alzheimer's Disease

IBM researchers then used NLP to analyse the participants' language sample transcripts. The model picked up tiny subtleties and changes in discourses that are generally missed if done manually. Based on this, IBM researchers trained the ML model to account for multiple variables affecting the results. Lastly, they drew on data from the subjects at the Framingham Heart Study, where the participants are assessed through two-minute Mini-Mental State Examination speech tests every four years and neuropsychological exams every year. CTT examples from FHS, including an unimpaired sample (a), an impaired sample showing telegraphic speech and lack of punctuation (b), and an even more impaired sample showing in addition significant misspellings and minimal grammatical complexity, e.g.