A method of building classifiers for neurological assessment is described. The method comprises the steps of extracting quantitative features from a plurality of clinical features, and selecting a subset of features from the extracted pool of features to construct binary classifiers. A device for performing point-of-care neurological assessment using clinical features is also described.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of building a classifier for assessment of a subject's neurological condition, comprising the steps of: providing a processing device operatively connected to a memory device storing a reference database of clinical results collected from one or more neurocognitive and/or clinical symptoms assessments performed on a plurality of individuals in the presence or absence of brain abnormalities, the processing device comprising a processor configured to perform the steps of: extracting quantitative features from the clinical results; storing the extracted features in a pool of selectable features; selecting a subset of features from the pool of selectable features; constructing a classifier using the subset of features; and determining classification accuracy of the classifier by using it to classify data records having a priori classification information. 2. The method of claim 1, further comprising the step of applying one or more data reduction criteria to the pool of selectable features to create a reduced pool of features from which the subset of features for constructing the classifier are selected. 3. The method of claim 1, wherein the neurocognitive assessment is performed using a dynamic questionnaire designed to change questions based on answers provided to prior questions. 4. The method of claim 1, wherein the neurocognitive assessment is performed using a standardized questionnaire. 5. The method of claim 1, wherein the quantitative features include one or more of severity ranking of symptoms, binary metric indicating presence or absence of symptoms, and normalized combinations of symptoms. 6. The method of claim 1, wherein the subset of features are selected using an evolutionary algorithm. 7. The method of claim 6, wherein the evolutionary algorithm applied is a genetic algorithm. 8. The method of claim 7, wherein the selected subset of features is optimized using at least one of a Random Mutation Hill Climbing algorithm and a Modified Random Mutation Hill Climbing algorithm. 9. The method of claim 1, wherein the subset of features is selected using a Simple Feature Picker algorithm 10. The method of claim 9, wherein the selected subset of features is optimized using at least one of a Random Mutation Hill Climbing algorithm and a Modified Random Mutation Hill Climbing algorithm. 11. The method of claim 1, wherein the classifier is a Linear Discriminant Function. 12. The method of claim 1, wherein the classifier is a Quadratic Discriminant Function. 13. The method of claim 1, wherein an objective function is used to evaluate the performance of the classifier. 14. The method of claim 13, wherein the objective function used is Area Under the Receiver Operating Curve of the classifier. 15. The method of claim 1, wherein the classifier is a binary classifier. 16. The method of claim 1, further comprising the step of imputing values for missing clinical results of the plurality of individuals in the population reference database. 17. The method of claim 1, wherein the references database further comprises clinical results from physiological tests. 18. The method of claim 1, wherein the reference database further comprises clinical results from neurophysiological assessments. 19. The method of claim 1, wherein the reference database comprises clinical results from brain electrical signals measurements. 20. A device for assessing a subject's neurological condition, the device comprising: an input device configured to acquire clinical results of one or more neurocognitive and/or clinical symptoms assessments performed on the subject; a processor operatively coupled to the input device, the processor configured to perform the steps of: extracting quantitative features from the clinical results of the one or more neurocognitive and/or clinical symptoms assessments performed on the subject; and applying a classifier to perform classification of the subject's neurological condition into one of two or more categories. 21. The method of claim 20, wherein the clinical results of the one or more neurocognitive and/or clinical symptoms assessments are entered manually into the input device by a user. 22. The method of claim 20, wherein the clinical results of the one or more neurocognitive and/or clinical symptoms assessments are acquired by the input device wirelessly or through a wired connection. 23. The device of claim 20, further comprising a memory device for storing interactive instructions for using and operating the device. 24. The device of claim 20, wherein the memory device stores a dynamic questionnaire that provides step-by-step instructions for performing the one or more neurocognitive and/or clinical symptoms assessments. 25. The device of claim 20, wherein the memory device stores a standardized questionnaire that provides step-by-step instructions for performing the one or more neurocognitive and/or clinical symptoms assessments. 26. The device of claim 20, further comprising a touch-screen interface to enter user input. 27. The device of claim 20, wherein the classifier comprises one or more discriminant functions. 28. The device of claim 20, wherein the classifier is a binary classifier.