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Article . 2021
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Fuzzification Based Osteoporosis Prediction Model

Authors: Kumar Shilpa; Shubangi D C;

Fuzzification Based Osteoporosis Prediction Model

Abstract

Osteoporosis is a disease in which bones become fragile and more likely to break. Osteoporosis can progress painlessly until it causes a bone fracture or a bone break. Dual Energy X-ray Absorptiometry (DEXA) is more costly and not accessible easily so we are using Fuzzy Inference system to predict osteoporosis. In this fuzzy logic, we collect risk factors and rules for osteoporosis and build a interface which take inputs and predicts if a person has osteoporosis. In the following Literature survey, we will take risk factors, rules, and ways to implement them. Around the world, 33% of women and 20% men over the age of 50 will suffer a fracture caused by Osteoporosis. Osteoporosis is a disease in which Bones become shallow and are fractured. If predicted before, quality of life will increase and severe surgery may be avoided.

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Keywords

Osteoporosis, Fuzzy-logic, Risk-Factors, Rules

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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