机器学习在医疗数据发展中的应用思考

Reflections on the Application of Machine Learning in the Development of Medical Data

随着互联网技术的发展,大数据依然成为当今医疗行业的战略资源。本文基于机器学习算法K近邻、支持向量机、Catboost对公开数据威斯康星州乳腺癌诊断数据进行建模实验,从实践角度深入了解机器学习算法在健康医疗数据中的应用,为当前的医学瓶颈提供新的思路。

With the development of Internet technology, big data is still a strategic resource for today’s medi-cal industry. Based on the machine learning algorithm K-nearest neighbor, support vector machine, and Catboost, this paper conducts modeling experiments on the public data of Wisconsin breast cancer diagnosis data, and deeply understands the application of machine learning algorithms in health and medical data from a practical point of view, and provides new insights for the current medical bottleneck.