Latest AI and machine learning research in health policy for healthcare professionals.
This study developed a support vector machine (SVM) algorithm-based prediction model with considering influence factors associated with the swallowing quality-of-life as the predictor variables and provided baseline information for enhancing the swallowing quality of elderly people's lives in the future. This study sampled 142 elderly people equal to or older than 65 years old who were using a s...
This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services based on air quality and machine learning. Hemorrhagic stroke, air quality, and meteorological data for 2016-2017 were obtained from the Longquanyi District of China, and the study included 1932 cases. Six machine learning methods were used to forecast the demand for hemorrhagic stroke healthcare serv...
Systematic, structured and longitudinal collection of realtime Big Patient Data and the analysis of aggregated diagnostic, therapeutic and therapy res...
The evidence that quality of life is a positive variable for the survival of cancer patients has prompted the interest of the health and pharmaceutica...
BACKGROUND: In this age of big data, certain models require very large data stores in order to be informative and accurate. In many cases however, the...
The domain of healthcare has always been flooded with a huge amount of complex data, coming in at a very fast-pace. A vast amount of data is generated...
Named Entity Recognition (NER) in the healthcare domain involves identifying and categorizing disease, drugs, and symptoms for biosurveillance, extrac...
Sleep quality is an important health indicator, and the current measurements of sleep rely on questionnaires, polysomnography, etc., which are intrusi...
Artificial Intelligence (AI) is evolving rapidly in healthcare, and various AI applications have been developed to solve some of the most pressing pro...
PURPOSE: Globally, individuals living with mental disorders are more likely to have access to a mobile phone than mental health care. In this commenta...
Hospital readmission is among the most critical issues in the healthcare system due to its high prevalence and cost. The improvement effort necessitat...
In many deep neural networks for pattern recognition, the input pattern is classified in the deepest layer based on features extracted through interme...
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm...
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two obj...
Sustainable urban development (SUD) requires a balance between economic growth, social well-being, and environmental protection. Oftentimes, urban pol...
The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessme...
As the airline industry has become ever-more competitive and profitability more tenuous, airline service quality management has grown more important t...
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaig...
Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF) patients that pose significant health risks and escalate care cost. I...
BACKGROUND: Technology-assisted clinical interventions are increasingly common in the health care field, often with the proposed aim to improve access...