Prediction of body mass index status from voice signals based on machine learning for automated medical applications

• Published in: Artificial intelligence in medicine Vol. 58; no. 1; pp. 51 - 61
• Main Authors: Lee, Bum Ju, Kim, Keun Ho, Ku, Boncho, Jang, Jun-Su, Kim, Jong Yeol
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.05.2013; Elsevier
• Subjects: Adult; Age Factors; Algorithms; Applied sciences; Artificial Intelligence; Biological and medical sciences; Body Mass Index; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Computerized, statistical medical data processing and models in biomedicine; Data processing. List processing. Character string processing; Exact sciences and technology; Female; Humans; Internal Medicine; Logistic Models; Male; Medical computing and teaching; Medical management aid. Diagnosis aid; Medical sciences; Memory organisation. Data processing; Middle Aged; Multi-class prediction; Obesity - diagnosis; Other; Overweight - diagnosis; Republic of Korea; Sex Factors; Software; Voice; Voice signals; Republic of Korea; Body mass index; Voice signals; Multi-class prediction; Obesity diagnosis; Measurement; Prognosis; Sex; Voiced signal; Male; Modeling; Variance; Aggregate model; Biomedical data processing; Diagnosis; Skewed distribution; Age; Medical application; Monitoring; Multiple classification; Obesity; Data analysis; Statistical analysis; Probabilistic approach; Regression analysis; Experimental study; Real time; Random decision forests; Variance analysis; Logistic regression; Treatment; Voice

The body mass index (BMI) provides essential medical information related to body weight for the treatment and prognosis prediction of diseases such as cardiovascular disease, diabetes, and stroke. We propose a method for the prediction of normal, overweight, and obese classes based only on the combi...