Machine Learning for Clinical Predictive Analytics
원문 초록
In this chapter, we provide a brief overview of applying machine learning techniques for clinical prediction tasks. We begin with a quick introduction to the concepts of machine learning and outline some of the most common machine learning algorithms. Next, we demonstrate how to apply the algorithms with appropriate toolkits to conduct machine learning experiments for clinical prediction tasks. The objectives of this chapter are to (1) understand the basics of machine learning techniques and the reasons behind why they are useful for solving clinical prediction problems, (2) understand the intuition behind some machine learning models, including regression, decision trees, and support vector machines, and (3) understand how to apply these models to clinical prediction problems using publicly available datasets via case studies.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Machine Learning Approach for Employee Retention Prediction
Earthquake magnitude prediction in Hindukush region using machine learning techniques
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins
Cautious Next Token Prediction
Where, What, Why: Towards Explainable Driver Attention Prediction
Out-of-Distribution Semantic Occupancy Prediction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.