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Buddi Inc machine-learning algorithm
Machine Learning Algorithm, supplied by Buddi Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine+learning+algorithms/machine+learning+algorithm/pm32357833-248-14-4
Average 90 stars, based on 1 article reviews
machine-learning algorithm - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Intraoperative hemodynamic management in abdominal aortic surgery guided by the Hypotension Prediction Index: the Hemas multicentric observational study.
Article Snippet: Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K et al (2018) Machinelearning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis.

Article Title: Estimating Blood Pressure during Exercise with a Cuffless Sphygmomanometer.
Article Snippet: Hatib, F.; Jian, Z.; Buddi, S.; Lee, C.; Settels, J.; Sibert, K.; Rinehart, J.; Cannesson, M. Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis.

Article Title: A review of machine learning methods for non-invasive blood pressure estimation.
Article Snippet: emphasized in perioperative care, where acute hypotension may affect vital organs like the heart, kidneys, and brain [2].. Clinically, blood pressure typically refers to arterial blood pressure (ABP) measured at the radial artery [10].. The invasive arterial line method, which involves inserting a small catheter directly into an artery, is considered the gold standard for blood pressure measurement and provides continuous monitoring [11–13].

Article Title: An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability.
Article Snippet: Hatib, F.; Jian, Z.; Buddi, S.; Lee, C.; Settels, J.; Sibert, K.; Rinehart, J.; Cannesson, M. Machine-Learning Algorithm to Predict Hypotension Based on High-Fidelity Arterial Pressure Waveform Analysis.

Article Title: Machine learning based analysis and detection of trend outliers for electromyographic neuromuscular monitoring.
Article Snippet: Neuromuscular blocking agents (NMBAs) form a pivotal drug category in daily perioperative anaesthesia management.. The monitoring of the clinical effect of these agents is essential to prevent postoperative residual neuromuscular block and ultimately postoperative pulmonary complications [1, 2].. Despite significantly decreasing the incidence of residual neuromuscular block, objective (quantitative) neuromuscular monitoring is still sub optimally used by Michaël Verdonck and Hugo Carvalho contributed equally to this work.

Article Title: An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram.
Article Snippet: Background and Objective: Carotid-femoral pulse wave velocity (cf-PWV) is the gold standard for noninvasive assessment of aortic stiffness.. Photoplethysmography used in wearable devices provides an indirect measurement method for cf-PWV.. This study aimed to construct a cf-PWV prediction method based on the XGBoost algorithm and wrist photoplethysmogram (wPPG) for the early screening of arteriosclerosis in primary healthcare.

Article Title: Performance of the Hypotension Prediction Index May Be Overestimated Due to Selection Bias
Article Snippet: Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K, Rinehart J, Cannesson M: Machine-learning algorithm Copyright © 2022, the American Society of Anesthesiologists.

Article Title: Hypotension prediction index: comparison between invasive and non-invasive pressure inputs.
Article Snippet: Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K, Rinehart J, Cannesson M. Machine-learning algorithm to predict hypotension based on High-fidelity arterial pressure waveform analysis.



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