Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GOLD) is only available for patients in stable phase. Currently, there is a lack of assessment and pre...
BMC medical informatics and decision making
Feb 6, 2020
BACKGROUND: A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects relevant to the organization...
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...
PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health r...
IMPORTANCE: Accurate risk stratification of patients with heart failure (HF) is critical to deploy targeted interventions aimed at improving patients' quality of life and outcomes.
Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning process for general medical hospital inpatients. It is possible that machine learning, using natural language processing, may be able to assist with ac...
BACKGROUND: In the hospital setting, it is crucial to identify patients at risk for deterioration before it fully develops, so providers can respond rapidly to reverse the deterioration. Rapid response (RR) activation criteria include a subjective co...
BACKGROUND: The triage of patients in prehospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study validates a ma...
Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical complications. But it is preventable and potentially reversible with early diagnosis and management. Therefore, several machine learning based predicti...