Machine learning for enhanced healthcare: an overview for operational and clinical leads

Abstract

Machine learning has the potential to transform how healthcare is delivered. It can support clinical decision making, determine the risk, presence and prognosis of disease and help optimise patient pathways. Widespread use and access to digital health records mean implementing machine learning models is quicker and easier than ever before. It is imperative for clinical and operational leads to understand the principles behind machine learning, so they can evaluate how it may be helpful to them and their teams. This article provides an overview of machine learning and how it can be used to help solve common healthcare-related problems.

Potable Water Identification with Machine Learning: An Exploration of Water Quality Parameters

“…For example, machine learning algorithms can be used to envisage patient outcomes, identify patients at high risk of complications, and optimize treatment plans. Additionally, machine learning can be used to improve medical imaging by identifying diseases and detecting abnormalities [21][22][23][24]. As a result, healthcare providers are able to deliver more effective and efficient care to patients.In transportation, machine learning is used to improve safety and efficiency.…”