Neuropsychiatric manifestations in childhood-onset systemic lupus erythematosus.

Neuropsychiatric manifestations occur frequently and are challenging to diagnose in childhood-onset systemic lupus erythematosus (SLE). Most patients with childhood-onset SLE have neuropsychiatric events in the first 2 years of disease. 30-70% of patients present with more than one neuropsychiatric event during their disease course, with an average of 2-3 events per person.

Axonal dysfunction is associated with interferon-γ levels in childhood-onset systemic lupus erythematosus: a multivoxel magnetic resonance spectroscopy study.

Objective: Axonal/neuronal damage has been shown to be a pathological finding that precedes neuropsychiatric manifestations in SLE. The objective of this study was to determine the presence of axonal dysfunction in childhood-onset SLE patients (cSLE) and to determine clinical, immunological and treatment features associated with its occurrence.

Methods: We included 86 consecutive cSLE patients [median age 17 (range 5-28) years] and 71 controls [median age 18 (5-28) years].

Proton magnetic resonance spectroscopy (H-MRS) in rheumatic autoimmune diseases: A systematic review.

Background/purpose: Proton magnetic resonance spectroscopy (H-MRS) has been shown to be an important non-invasive tool to quantify neuronal loss or damage in the investigation of central nervous system (CNS) disorders. The purpose of this article is to discuss the clinical utility of H-MRS in determining CNS involvement in individuals with rheumatic autoimmune diseases.

Methods: This study is a systematic review of the literature, conducted during the month of November and December of 2019 of articles published in the last 16 years (2003-2019).

A survey on computer-assisted Parkinson's Disease diagnosis.

Background And Objective: In this work, we present a systematic review concerning the recent enabling technologies as a tool to the diagnosis, treatment and better quality of life of patients diagnosed with Parkinson's Disease (PD), as well as an analysis of future trends on new approaches to this end.

Methods: In this review, we compile a number of works published at some well-established databases, such as Science Direct, IEEEXplore, PubMed, Plos One, Multidisciplinary Digital Publishing Institute (MDPI), Association for Computing Machinery (ACM), Springer and Hindawi Publishing Corporation. Each selected work has been carefully analyzed in order to identify its objective, methodology and results.

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification.

Background And Objective: Parkinson's disease (PD) is considered a degenerative disorder that affects the motor system, which may cause tremors, micrography, and the freezing of gait. Although PD is related to the lack of dopamine, the triggering process of its development is not fully understood yet.

Methods: In this work, we introduce convolutional neural networks to learn features from images produced by handwritten dynamics, which capture different information during the individual's assessment.

A new computer vision-based approach to aid the diagnosis of Parkinson's disease.

Background And Objective: Even today, pointing out an exam that can diagnose a patient with Parkinson's disease (PD) accurately enough is not an easy task. Although a number of techniques have been used in search for a more precise method, detecting such illness and measuring its level of severity early enough to postpone its side effects are not straightforward. In this work, after reviewing a considerable number of works, we conclude that only a few techniques address the problem of PD recognition by means of micrography using computer vision techniques.