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Congratulations to the amazing team for their work on the novel machine learning technique published in eLife!!!
A multidisciplinary team of data scientist, researchers and expert clinicians collaborated to provide new guidance in spinal cord injured patient care. In this multi-center study, Dr. Torres-Espin and team analyzed data from multiple published and unpublished studies to suggest an optimal mean arterial pressure during SCI surgery. Maintaining the patients mean blood pressure between 76 mmHg and 104–117mmHg was found to have a higher likelihood of motor function recovery.
You can read more here: https://elifesciences.org/for-the-press/351f455c/precise-blood-pressure-control-may-aid-patient-recovery-from-spinal-injury and watch the video here:https://sanfrancisco.cbslocal.com/2021/11/19/data-ucsf-researchers-treatment-spinal-injuries/
For the related datasets check out public datasets section @ODC-SCI.
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Spinal cord injury (SCI) produces a complex syndrome characterized by loss of motor control and mobility; loss of bladder, bowel and sexual function; pathological pain; and loss of autonomy. The multifaceted nature of SCI presents a challenge for the translational pipeline. This problem of SCI complexity can be conceptualized as a big-data issue: the field needs a forum for large-scale data-sharing and application of advanced analytics to catalyze SCI discoveries. Various funders and publishers have recognized this need as well currently implementing data sharing mandates.
To address this challenge the SCI research community is assembling a large database through collaborative and FAIR data sharing. We are a digital infrastructure with the goal to democratize SCI data, allowing researchers to access existing SCI data, contribute their own, and publish with citable DOI. Learn more
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