AIMC Topic: Health Services Needs and Demand

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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine Nov 20, 2018
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Adult Male Middle Aged Risk Assessment Risk Factors Aged Aged, 80 and over Young Adult Health Status Age Factors Emergency Service, Hospital Data Mining England Adolescent Time Factors Socioeconomic Factors Humans Machine Learning Electronic Health Records Female Reproducibility of Results Sex Factors Health Services Needs and Demand Patient Admission Needs Assessment
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Estimation of the Basic Reproduction Number and Vaccination Coverage of Influenza in the United States (2017-18).

Journal of research in health sciences Sep 22, 2018
BACKGROUND: Determining the epidemic threshold parameter helps health providers calculate the coverage while guiding them in planning the process of vaccination strategy. Since the trend and mechanism of influenza is very similar in different countri...
Epidemics Bayes Theorem Vaccination Coverage Humans Influenza, Human Health Services Needs and Demand Vaccination Basic Reproduction Number United States
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An ensemble boosting model for predicting transfer to the pediatric intensive care unit.

International journal of medical informatics Jan 9, 2018
BACKGROUND: Early deterioration indicators have the potential to alert hospital care staff in advance of adverse events, such as patients requiring an increased level of care, or the need for rapid response teams to be called. Our work focuses on the...
Health Services Needs and Demand Patient Transfer Child, Hospitalized Child Intensive Care Units, Pediatric ROC Curve Models, Statistical Female Male Severity of Illness Index Humans Artificial Intelligence Machine Learning Algorithms Retrospective Studies
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Chaotic genetic algorithm and Adaboost ensemble metamodeling approach for optimum resource planning in emergency departments.

Artificial intelligence in medicine Oct 18, 2017
Long length of stay and overcrowding in emergency departments (EDs) are two common problems in the healthcare industry. To decrease the average length of stay (ALOS) and tackle overcrowding, numerous resources, including the number of doctors, nurses...
Humans Neural Networks, Computer Machine Learning Decision Support Techniques Computer Simulation Length of Stay Time Factors Emergency Service, Hospital Needs Assessment Decision Support Systems, Management Delivery of Health Care, Integrated Workflow Health Services Needs and Demand Hospitals, Teaching Patient Discharge Patient Admission Efficiency, Organizational Patient Care Team Nonlinear Dynamics
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A comparison of rule-based and machine learning approaches for classifying patient portal messages.

International journal of medical informatics Jun 23, 2017
OBJECTIVE: Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal mess...
Natural Language Processing Bayes Theorem Health Services Needs and Demand Patient Portals Machine Learning Health Personnel Electronic Health Records Communication Humans
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Automated Classification of Consumer Health Information Needs in Patient Portal Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Patients have diverse health information needs, and secure messaging through patient portals is an emerging means by which such needs are expressed and met. As patient portal adoption increases, growing volumes of secure messages may burden healthcar...
Health Services Needs and Demand Consumer Health Information Patient Portals Humans Electronic Health Records Health Resources Natural Language Processing
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Creating a place for caregivers in personal health: the iHealthSpace copilot program and diabetes care.

Journal of diabetes science and technology Jan 1, 2011
BACKGROUND: As America's baby boom generation reaches retirement, the number of elders, and, in turn, the number of lay individuals who support them, will continue to increase. With the important services caregivers provide, it is critical that we re...
Health Personal Health Services Personal Space Self-Help Groups Health Records, Personal Models, Biological Health Services Needs and Demand Caregivers Humans Pilot Projects Adult User-Computer Interface Diabetes Mellitus Internet
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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users.

BMC medical research methodology May 15, 2025
BACKGROUND: Supervised machine learning is increasingly being used to estimate clinical predictive models. Several supervised machine learning models involve hyper-parameters, whose values must be judiciously specified to ensure adequate predictive p...
Bayes Theorem Health Services Needs and Demand Monte Carlo Method Humans Health Care Costs Machine Learning Algorithms
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Machine learning approach for unmet medical needs among middle-aged adults in South Korea: a cross-sectional study.

BMC health services research May 13, 2025
BACKGROUND: South Korea is reported to have higher levels of unmet medical needs (UMN) than other countries, particularly among the middle-aged adult population. Considering that this group constitutes a substantial portion of the country's productiv...
Cross-Sectional Studies Male Middle Aged Bayes Theorem Machine Learning Republic of Korea Female Adult Health Services Needs and Demand Humans
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Characterizing Subgroups of High-Need, High-Cost Patients Based on Their Clinical Conditions: a Machine Learning-Based Analysis of Medicaid Claims Data.

Journal of general internal medicine Aug 1, 2019
Male Middle Aged United States Health Services Needs and Demand Health Care Costs Medicaid Humans Insurance Claim Review Machine Learning Female Adult
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