Blood Pressure Estimation Using Explainable Deep-Learning Models Based on Photoplethysmography.

Background: Due to their invasiveness, arterial lines are not typically used in routine monitoring, despite their superior responsiveness in hemodynamic monitoring and detecting intraoperative hypotension. To address this issue, noninvasive, continuous arterial pressure monitoring is necessary. We developed a deep-learning model that reconstructs continuous mean arterial pressure (MAP) using the photoplethysmograhy (PPG) signal and compared it to the arterial line gold standard.

Measuring Indigenous food security-A case for Indigenous designed tools.

Food insecurity disproportionately impacts Indigenous peoples, leading to significant health disparities. Indigenous peoples globally share a deep and interconnected relationship to their lands, waterways and seas that ensures optimum health, and cultural, spiritual, social and emotional wellbeing. However, food security definitions and assessment frameworks in research and policy predominantly stem from capitalist and colonial food system values.

Estimating Coronary Sinus Oxygen Saturation from Pulmonary Artery Oxygen Saturation.

: Coronary sinus oxygen saturation is a useful indicator of health and disease states. However, it is not routinely used in clinical practice. Cardiovascular magnetic resonance imaging (CMR) oximetry can accurately estimate oxygen saturation in the pulmonary artery.

Monitoring Guideline Adherence in Severe Traumatic Brain Injury.

Traumatic brain injuries (TBI) significantly impact global health, often resulting in death or long-term disability. We developed a quality dashboard to monitor adherence to severe TBI guidelines, leveraging data from Rennes University Hospital's clinical data warehouse collected between January 2020 and December 2023. We included 193 patients from the surgical ICU who were over 18 years old and excluded those without adequate intracranial pressure (ICP) monitoring data.