Handbook of Decision Support Systems for Neurological Disorders

1.A review of deep learning-based disease detection in Alzheimer’s patients<br>2. Brain tissue segmentation to detect schizophrenia in gray matter using MR images<br>3. Detection of small tumors of the brain using medical imaging<br>4. Fuzzy logic-based hybrid knowledge systems for the detection and diagnosis of childhood autism<br>5. Artificial intelligence for risk prediction of Alzheimer’s disease: a new promise for community health screening in the<br>older aged<br>6. Cost-effective assistive device for motor neuron disease <br>7. EEG signal-based human emotion detection using an artificial neural network<br>8. Multiview decision tree-based segmentation of tumors in MR brain medical images<br>9. Multiclass SVM coupled with optimization techniques for<br>segmentation and classification of medical images<br>10. Brain tissues segmentation in magnetic resonance imaging for the diagnosis of brain disorders using a convolutional neural network<br>11. Fine motor skills and cognitive development using virtual reality-based games in children<br>12. A CAD software application as a decision support system for ischemic stroke detection in the posterior fossa<br>13. Optimization-based multilevel threshold image segmentation for identifying ischemic stroke lesion in brain MR images<br>14. A study of machine learning algorithms used for detecting cognitive disorders associated with dyslexia<br>15. A Critical Analysis and Review of Assistive Technology: Advancements, Laws, and Impact on Improving the Rehabilitation of Dysarthric Patients<br>16. A comparative study on the application of machine learning<br>algorithms for neurodegenerative disease prediction