Parkinson’s disease is lacking easily accessible biomarkers. Here the authors show, that targeted blood proteomics is feasible to identify the patients and to predict the phenoconvertion in prodromal subjects up to 7 years before symptom onset.
If I’m understanding this right, they used a machine learning algorithm to identify some markers in the blood of Parkinson’s patients, and now they’re testing for those markers. The AI in question is ML, and isn’t involved in the actual testing.
If I’m understanding this right, they used a machine learning algorithm to identify some markers in the blood of Parkinson’s patients, and now they’re testing for those markers. The AI in question is ML, and isn’t involved in the actual testing.