Accuracy Improvement for Predicting Parkinson’s Disease Progression
نویسندگان
چکیده
منابع مشابه
Accuracy Improvement for Predicting Parkinson’s Disease Progression
Parkinson's disease (PD) is a member of a larger group of neuromotor diseases marked by the progressive death of dopamineproducing cells in the brain. Providing computational tools for Parkinson disease using a set of data that contains medical information is very desirable for alleviating the symptoms that can help the amount of people who want to discover the risk of disease at an early stage...
متن کاملRab11 in Disease Progression
Membrane/ protein trafficking in the secretory/ biosynthetic and endocytic pathways is mediated by vesicles. Vesicle trafficking in eukaryotes is regulated by a class of small monomeric GTPases the Rab protein family. Rab proteins represent the largest branch of the Ras superfamily GTPases, and have been concerned in a variety of intracellular vesicle trafficking and different intracellular sig...
متن کاملPredicting the Keratoconus Disease Severity Based on Pachymetric Progression Indices Measured by Pentacam
Background Keratoconus (KCN) is a bilateral, progressive, and non-inflammatory disorder in the cornea, which results in thinning and protrusion of the cornea. Objective This study aims to determine the effectiveness of using pachymetric progression indices (PPIs) in grading the severity of KCN disease. Methods In this study, 76 patients with different stages of KCN were enrolled. The severit...
متن کاملAccuracy of ultrasonography in predicting celiac disease.
BACKGROUND Various ultrasonographic (US) signs have been reported in overt celiac disease (CD). The aim of this study was to investigate the diagnostic accuracy of 6 US parameters in predicting CD. METHODS One hundred sixty-two consecutive patients with chronic diarrhea (n=105), iron deficiency anemia (n=25), or dyspepsia (n=32) underwent anti-endomysial IgA antibody determination and duodena...
متن کاملPredicting disease progression in amyotrophic lateral sclerosis
OBJECTIVE It is essential to develop predictive algorithms for Amyotrophic Lateral Sclerosis (ALS) disease progression to allow for efficient clinical trials and patient care. The best existing predictive models rely on several months of baseline data and have only been validated in clinical trial research datasets. We asked whether a model developed using clinical research patient data could b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2016
ISSN: 2045-2322
DOI: 10.1038/srep34181