🫁 The world's first open-source ventilator tested on human patients. Mass-producible at a low cost (~2000€).
Machine Learning for Patient Risk Stratification for Acute Respiratory Distress Syndrome (Zeiberg & Prahlad et al.), PLOS ONE, March 2019. https://doi.org/10.1371/journal.pone.0214465
Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients
A PyTorch Wrapper of Hierarchical Attention Network with Sentence Objectives Framework for ARDS Identification
Machine Learning to predict ARDS from Chest X-Ray images and Medical Data
Reproducible analysis of cross-compartment microbiome signals and recorded ARDS in acute pancreatitis
Multiscale computational respiratory simulator modeling nonlinear alveolar viscoelasticity, inhomogeneous ventilation-perfusion mismatch, pendelluft gas redistribution, and patient-ventilator asynchrony in acute respiratory distress syndrome.
Reproducible pipeline for early incident ARDS prediction in MIMIC-IV: cohort extraction, label definition, baseline / multimodal / dynamic models and evaluation.
A structured clinical reasoning portfolio for medical school preparation, documenting progressive ICU case analysis across hemodynamics, shock management, ventilation strategies, neurocritical care, and trauma. All cases are hypothetical and used for premedical academic development.
Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients
Analysis of host regulatory networks that could be impacted upon infection with the Covid-19 virus
Open reliability atlas of the Pulse Physiology Engine 4.3.1: Morris sensitivity analysis, failure-mode flags and a reproducible pipeline (code, data artefacts and audit ledger of the arXiv preprint).
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