Predicting Patient-ventilator Asynchronies with Hidden Markov Models
Sign Up to like & getrecommendations! Published in 2018 at "Scientific Reports"
DOI: 10.1038/s41598-018-36011-0
Abstract: In mechanical ventilation, it is paramount to ensure the patient’s ventilatory demand is met while minimizing asynchronies. We aimed to develop a model to predict the likelihood of asynchronies occurring. We analyzed 10,409,357 breaths from… read more here.
Keywords: hidden markov; risk; patient ventilator; predicting patient ... See more keywords
Predicting patient acuity according to their main problem
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DOI: 10.1111/jonm.12885
Abstract: Abstract Aim To assess the ability of the patient main problem to predict acuity in adults admitted to hospital wards and step‐down units. Background Acuity refers to the categorization of patients based on their required… read more here.
Keywords: acuity; predicting patient; patient acuity; main problem ... See more keywords
‘Can I trust my patient?’ Machine Learning support for predicting patient behaviour
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DOI: 10.1136/jme-2023-109094
Abstract: on the risks of testimonial injustice when using automated prediction drug read more here.
Keywords: learning support; trust patient; patient machine; support predicting ... See more keywords
Predicting patient experience of Invisalign treatment: An analysis using artificial neural network
Sign Up to like & getrecommendations! Published in 2022 at "Korean Journal of Orthodontics"
DOI: 10.4041/kjod21.255
Abstract: Objective Poor experience with Invisalign treatment affects patient compliance and, thus, treatment outcome. Knowing the potential discomfort level in advance can help orthodontists better prepare the patient to overcome the difficult stage. This study aimed… read more here.
Keywords: patient experience; invisalign treatment; predicting patient; treatment ... See more keywords