Survey of Machine Learning Algorithms for Disease Diagnostic

• 作者: Maruf Pasha Meherwar Fatima
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 医学
• 关键词: MACHINE LEARNING Artificial INTELLIGENCE MACHINE LEARNING TECHNIQUES
• 年，卷（期）: 2017,（1）
• 页码范围: 1-16
• 页数: 16页
• 分类号: R73

摘要

In medical imaging, Computer Aided Diagnosis (CAD) is a rapidly growing dynamic area of research. In recent years, significant attempts are made for the enhancement of computer aided diagnosis applications because errors in medical diagnostic systems can result in seriously misleading medical treatments. Machine learning is important in Computer Aided Diagnosis. After using an easy equation, objects such as organs may not be indicated accurately. So, pattern recognition fundamentally involves learning from examples. In the field of bio-medical, pattern recognition and machine learning promise the improved accuracy of perception and diagnosis of disease. They also promote the objectivity of decision-making process. For the analysis of high-dimensional and multimodal bio-medical data, machine learning offers a worthy approach for making classy and automatic algorithms. This survey paper provides the comparative analysis of different machine learning algorithms for diagnosis of different diseases such as heart disease, diabetes disease, liver disease, dengue disease and hepatitis disease. It brings attention towards the suite of machine learning algorithms and tools that are used for the analysis of diseases and decision-making process accordingly.