Applying Machine Learning to Construct a Model of Risk of Depression in Patients Following Cardiac Surgery with the Use of the SF-12 Survey.

Katarzyna Nowicka-Sauer Krzysztof Jarmoszewicz Andrzej Molisz Krzysztof Sobczak Marta Sauer Mariusz Topolski

Published in: International journal of environmental research and public health (2023)

Assessing fatigue and vitality can help health professionals with identifying patients at risk of depression. In addition, assessing functional status and dimensions of fatigue, as well as the impact of emotional state on daily functioning, can help determine effective intervention options.

Keyphrases

sleep quality
machine learning
cardiac surgery
end stage renal disease
depressive symptoms
randomized controlled trial
newly diagnosed
ejection fraction
chronic kidney disease
acute kidney injury
cross sectional
peritoneal dialysis
big data
patient reported outcomes
patient reported