Avancerad sökning

Visar resultat 16 - 20 av 51 uppsatser som matchar ovanstående sökkriterier.

  1. 16. Prioritization of Informative Regions in PET Scans for Classification of Alzheimer's Disease

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Fredrik Mårtensson; Erik Westberg; [2021]
    Nyckelord :;

    Sammanfattning : Alzheimer’s Disease (AD) is a widespread neurodegenerative disease. The disease causes brain atrophy, resulting in memory loss, decreased cognitive ability, and eventually death. There is currently no cure for the disease, but treatment may delay the onset. Therefore, it is crucial to detect the disease at an early stage. LÄS MER

  3. 17. Determining linguistic predictor for the classification of subjective cognitive impairment and mild cognitive impairment using machine learning

    Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori

    Författare :Tian Wang; [2020-09-01]
    Nyckelord :mild cognitive impairment; sibjective cognitive impairment; natural language processing; support vector machine; neural networks;

    Sammanfattning : Introduction Mild Cognitive Impairment (MCI) is a neurological condition characterized by cognitive decline greater than expected for an individual's age and education level. Subjective Cognitive Impairment (SCI) is a selfreported decline in cognitive abilities but not clinically identified as MCI. LÄS MER

  4. 18. Potential Neurophysiological Biomarkers for the Diagnosis of Age-related Neurodegenerative Diseases

    Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskap

    Författare :Veronika Marková; [2020]
    Nyckelord :dementia; Alzheimer’s disease; frontotemporal dementia; TMSevoked potentials; motor-evoked potentials; mild cognitive impairment; aging; diagnosis;

    Sammanfattning : The global population with dementia is rapidly increasing around the world.The major risk factor for dementia is aging. There is currently no treatmentavailable and the cost of symptomatic treatment is high. LÄS MER

  5. 19. An implementation analysis of a machine learning algorithm on eye-tracking data in order to detect early signs of dementia

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jennifer Lindberg; Henrik Siren; [2020]
    Nyckelord :Dementia; Eye-tracking; Machine Learning; naïve Bayes.;

    Sammanfattning : This study aims to investigate whether or not it is possible to use a machine learning algorithm on eye-tracking data in order to detect early signs of Alzheimer’s disease, which is a type of dementia. Early signs of Alzheimer’s are characterized by mild cognitive impairment. LÄS MER

  7. 20. Impact of tractogram filtering and graph creation for structural connectomics in subjects with mild cognitive impairment

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Marvin Köpff; [2020]
    Nyckelord :Mild cognitive impairment; MCI; MRI; Tractography; Tractogram Filtering; SIFT; Graph Creation; Machine Learning; Classification;

    Sammanfattning : One particular challenge of brain connectomics deals with inferring differences in the brain due to diseases such as Alzheimer's. More specifically, structural connectomics aims at investigating the connectivity between regions in the brain based on the distribution of neuronal fibers. LÄS MER