Decision Trees for Predicting Brain Tumors: A Case Study in Health Care

被引:1
|
作者
Jayanthi, Prisilla
Krishna, Iyyanki V. Murali [1 ]
Pavani, B. [2 ]
Sushmita, C. [3 ]
Chandana, G. [4 ]
Esther, Y. Evangelyne
Susheela, Mary [5 ]
机构
[1] JNTUH, R&D, Hyderabad, India
[2] Mahatma Jyotiba Phule, Residential Educ Inst Soc, Mahaboobnagar, India
[3] KLE Univ, Jawaharlal Nehru Med Coll, Belgaum, India
[4] South East Missouri State Univ, Human Performance & Recreat Coll, Dept Hlth, Cape Girardeau, MO USA
[5] Suprabath Inst Management, Hyderabad, Telangana, India
关键词
Decision trees; Health care; Machine learning; Supervised learning;
D O I
10.1007/978-981-13-1165-9_83
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the wide expansion of unstructured health data records, there is a need to organize in an effective manner and easy data access. The top-down approach can automatically assign the unstructured health records into a hierarchy with prior domain knowledge. Decision trees are reliable providing high classification accuracy with a simple representation of collected knowledge and effective decision-making technique that can be used in medical care. Decision trees can handle huge datasets with simple and fast integration. It is easy to predict the classification of unseen records using decision tree.
引用
收藏
页码:921 / 928
页数:8
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