.png){kind=icon}
返回
Machine Learning and Health Science Research: Tutorial
.png){kind=icon}
OA
AI
DOI：10.2196/50890.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health science researchers in understanding the strengths and limitations of ML and to facilitate its integration into their studies, we present here a guideline for integrating ML into an analysis through a structured framework, covering steps from framing a research question to study design and analysis techniques for specialized data types.
Keyword:
health science researcher
machine learning pipeline
machine learning
medical machine learning
precision medicine
reproducibility
unsupervised learning
期刊
IF:
6
论文数:
9.7K
被引数:
5.0W
机构
引用论文
.png){kind=icon}
Matrix Effects in the Detection of Pb and Ba in Soils Using Laser-Induced Breakdown Spectroscopy使用激光诱导击穿光谱检测土壤中Pb和Ba的基质效应
PREAI
分享收藏分享收藏分享收藏Solubility Advantage of Pyrazine-2-carboxamide: Application of Alternative Solvents on the Way to the Future Pharmaceutical DevelopmentPyrazine-2-carboxamide的溶解度优势: 替代溶剂在未来药物开发中的应用
PREAI
分享收藏Analysis and assessment of ship collision accidents using Fault Tree and Multiple Correspondence Analysis基于故障树和多重对应分析的船舶碰撞事故分析与评估
PREAI
分享收藏
查看更多内容