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Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records
Conclusion: Electronic administrative records from this cohort produced reliable outcome prediction and identified clinically appropriate factors negatively impacting most outcome variables following hospital admission with stroke. This presents a means of future identification of modifiable factors associated with patient discharge destination. This may potentially aid in patient selection for certain interventions and aid in better patient and clinician education regarding expected discharge outcomes.
Source: Frontiers in Neurology - September 27, 2021 Category: Neurology Source Type: research

Neuroimmunology of Human T-Lymphotropic Virus Type 1-Associated Myelopathy/Tropical Spastic Paraparesis
Conclusion Recent advances in research on HTLV-1 provide better understanding of the molecular pathogenesis and mechanisms of HAM/TSP, and several clinical trials of novel therapies for patients with HAM/TSP have been initiated. However, long-term improvement of motor disability and quality of life still have not been achieved in HAM/TSP patients, and the clinical management remains challenging. Given that HAM/TSP is characterized by activated T-cells in both the periphery and CNS, studies in HAM/TSP will be highly informative for clarifying the pathogenesis of other neuroinflammatory disorders such as multiple sclerosis....
Source: Frontiers in Microbiology - April 23, 2019 Category: Microbiology Source Type: research