کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8686610 1580829 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Chained regularization for identifying brain patterns specific to HIV infection
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Chained regularization for identifying brain patterns specific to HIV infection
چکیده انگلیسی
Human Immunodeficiency Virus (HIV) infection continues to have major adverse public health and clinical consequences despite the effectiveness of combination Antiretroviral Therapy (cART) in reducing HIV viral load and improving immune function. As successfully treated individuals with HIV infection age, their cognition declines faster than reported for normal aging. This phenomenon underlines the importance of improving long-term care, which requires a better understanding of the impact of HIV on the brain. In this paper, automated identification of patients and brain regions affected by HIV infection are modeled as a classification problem, whose solution is determined in two steps within our proposed Chained-Regularization framework. The first step focuses on selecting the HIV pattern (i.e., the most informative constellation of brain region measurements for distinguishing HIV infected subjects from healthy controls) by constraining the search for the optimal parameter setting of the classifier via group sparsity (ℓ2,1-norm). The second step improves classification accuracy by constraining the parameterization with respect to the selected measurements and the Euclidean regularization (ℓ2-norm). When applied to the cortical and subcortical structural Magnetic Resonance Images (MRI) measurements of 65 controls and 65 HIV infected individuals, this approach is more accurate in distinguishing the two cohorts than more common models. Finally, the brain regions of the identified HIV pattern concur with the HIV literature that uses traditional group analysis models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 183, December 2018, Pages 425-437
نویسندگان
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