The invention relates to a
sarcopenia prediction model construction method and
system without physique measurement, and belongs to the field of medical
informatization. The method comprises the steps of establishing a crowd
data set, preprocessing sample data, dividing a
training set and a
test set, screening modeling features, constructing a plurality of
machine learning classifiers, selecting an optimal model, evaluating and
predicting performance and the like. The high-performance
sarcopenia prediction model can be constructed by only using information such as age, gender, height, weight and the like which can be obtained through
questions and answers or self-evaluation as independent variables without
physical fitness measurement such as
grip strength and
physical fitness test. The
system comprises a
data acquisition module, a
data analysis module and a result output module, can realize rapid, low-cost, remote and self-evaluation prediction of
sarcopenia risk, is suitable for scenes of various medical institutions, communities, families and the like at all levels, and is beneficial to early screening, intervention and
dynamic monitoring of sarcopenia.