Publications by authors named "M Shafizadeh"

RaceRunning is a sport for disabled people and successful performance depends on reducing the amount of time spent travelling a specific distance. Performance analysis in RaceRunning athletes is based on traditional methods such as recording race time, distances travelled and frequency (sets and reps) that are not sufficient for monitoring training loads. The aims of this study were to monitor training loads in typical training sessions and evaluate technical adaptations in RaceRunning performance by acquiring sensor metrics.

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  • Stroke is a major global health issue, with about one-third of patients facing a second stroke, prompting this study to explore machine learning (ML) algorithms for predicting recurrent strokes.
  • The study analyzed 12 research papers involving over 24,000 individuals, revealing that ML models have a sensitivity of 71% and a specificity of 88% for predicting recurrent strokes.
  • While the results are promising, indicating that ML could help identify high-risk patients, the study highlights the need for standardized methods and further research to improve the consistency and applicability of these predictive models.
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  • This study explores the predictive value of certain radiographic features for neurologic outcomes in patients with basilar artery occlusion (BAO) who undergo endovascular therapy, as prior trials only included specific patients based on prognostic scores.
  • It analyzes data from a thrombectomy database, correlating various demographic factors and radiographic scoring systems (PCCS, BATMAN, pc-ASPECTS) with 90-day neurologic outcomes, finding that lower scores on PCCS and BATMAN were linked to worse outcomes.
  • Results showed that 21.5% of patients had a good neurologic outcome after 90 days, with significant associations found between poor outcomes and existing infarcts in specific brain
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  • Glioma is a common type of brain tumor, and a specific mutation can indicate a better chance of recovery.
  • The study used machine learning to analyze data from 22 studies involving over 5,000 patients to see how well it could predict the mutation.
  • Results showed that machine learning is quite accurate in predicting the mutation status, but more work is needed to make it even better for doctors to use in treating patients.
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Introduction: Penetrating neck trauma (PNT) due to gunshot injuries is one of the challenging conditions with the potential for both significant morbidities and mortality.

Research Question: There are significant concerns in the approach to patients with spinal gunshot injuries. Surgery indications, methods of surgery, and management of CSF leaks are the main concerns of these patients.

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