Predicting body fat percentage based on gender, age and BMI by using artificial neural networks

Computer Methods and Programs in Biomedicine

Volumn 113, Issue 2, 2014, Pages 610-619

  Kupusinac, Aleksandar ^a   Stokić, Edita ^b   Doroslovački, Rade ^a  

^a UNIVERSITY OF NOVI SAD   (Serbia)

^b UNIVERSITY OF NOVI SAD   (Serbia)

Author keywords

Artificial neural networks; Body composition; Body fat percentage; Cardiovascular risk; Obesity

Indexed keywords

BIOELECTRICAL IMPEDANCE MEASUREMENTS; BODY COMPOSITION; BODY FATS; BODY MASS INDEX; CARDIOVASCULAR RISK; NON-INVASIVE PREDICTION; OBESITY; PREDICTIVE ACCURACY;

BIOCHEMISTRY; FORECASTING; NEURAL NETWORKS; NUTRITION; STATISTICAL TESTS;

HEALTH;

ACCURACY; ADULT; AGE DISTRIBUTION; AGED; ANTHROPOMETRY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BODY FAT; BODY HEIGHT; BODY MASS; CLINICAL PRACTICE; FEMALE; HEALTH CARE COST; HUMAN; IMPEDANCE; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; NERVE CELL; PREDICTION; SEX DIFFERENCE; VERY ELDERLY; YOUNG ADULT;

ARTIFICIAL NEURAL NETWORKS; BODY COMPOSITION; BODY FAT PERCENTAGE; CARDIOVASCULAR RISK; OBESITY;

ADIPOSE TISSUE; ADOLESCENT; ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; BODY MASS INDEX; FEMALE; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); SEX FACTORS; YOUNG ADULT;

EID: 84892827712     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.10.013     Document Type: Article

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