Listen "Conversation with Dr. Bart Geerts"
Episode Synopsis
Bart Geerts MD,PhD is a multi-specialty physician ( anaesthetist and intensivist), entrepreneur and researcher who aims to improve patient health and health care with artificial intelligence, mHealth and other med tech through empowerment and process optimization. Bart has over ten years of clinical experience as an anaesthetist, intensivist and clinical pharmacologist in the Netherlands and UK. He has managed a research group of more than ten scientists with a focus on medical technology and big data. Bart has studied medicine (MD), biomedical sciences (MSc), intensive care medicine (PhD), and global business (MBA).
Three years ago, Bart started Healhtplus.ai. This start-up of eight people is currently performing clinical trials at three European sites to study the impact of a machine-learning tool, called PERISCOPE, that predicts infections after surgery in adults. He is hoping to make a dent in one of the major problems occurring in surgical care today.
His landmark work with the hypotension prediction index was published last year in the JAMA and is leading to ongoing research and collaborative efforts for validation in different surgical and critical care populations the world over: Wijnberge M, Geerts BF, Hol L, Lemmers N, Mulder MP, Berge P, Schenk J, Terwindt LE, Hollmann MW, Vlaar AP, Veelo DP. Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. JAMA. 2020 Mar 17;323(11):1052-1060. doi: 10.1001/jama.2020.0592. PMID: 32065827; PMCID: PMC7078808.
Three years ago, Bart started Healhtplus.ai. This start-up of eight people is currently performing clinical trials at three European sites to study the impact of a machine-learning tool, called PERISCOPE, that predicts infections after surgery in adults. He is hoping to make a dent in one of the major problems occurring in surgical care today.
His landmark work with the hypotension prediction index was published last year in the JAMA and is leading to ongoing research and collaborative efforts for validation in different surgical and critical care populations the world over: Wijnberge M, Geerts BF, Hol L, Lemmers N, Mulder MP, Berge P, Schenk J, Terwindt LE, Hollmann MW, Vlaar AP, Veelo DP. Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. JAMA. 2020 Mar 17;323(11):1052-1060. doi: 10.1001/jama.2020.0592. PMID: 32065827; PMCID: PMC7078808.
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