AIMC Topic: Health Services Needs and Demand

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Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study.

JMIR cancer
BACKGROUND: Complementary therapies are being increasingly used by cancer survivors. As a channel for customers to share their feelings, outcomes, and perceived knowledge about the products purchased from e-commerce platforms, Amazon consumer reviews...

Evaluating forecasting models for health service demand during the COVID-19 pandemic.

Scientific reports
We combine daily internet search data and monthly information on medical expenditures for anti-depressants to test two distinct hypotheses in eight Australian states, covering the period from 2020 to 2022. First, whether using daily search data can h...

Predicting total healthcare demand using machine learning: separate and combined analysis of predisposing, enabling, and need factors.

BMC health services research
OBJECTIVE: Predicting healthcare demand is essential for effective resource allocation and planning. This study applies Andersen's Behavioral Model of Health Services Use, focusing on predisposing, enabling, and need factors, using data from the 2022...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

Scientific reports
This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affect the demand for medical and daily care services of the elderly. In this study, a questionnaire sur...

Leveraging Artificial Intelligence to Inform Care Coordination by Identifying and Intervening in Patients' Unmet Social Needs: A Scoping Review.

Journal of advanced nursing
AIM: We reviewed how artificial intelligence has been applied to inform care coordination by identifying and/or intervening in patients' unmet social needs.

Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

PloS one
During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. Providing real-time short-term forecasts of the demand for health care services helps managers plan t...

Identifying definite patterns of unmet needs in patients with multiple sclerosis using unsupervised machine learning.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
INTRODUCTION: People with multiple sclerosis (PwMS) exhibit a spectrum of needs that extend beyond solely disease-related determinants. Investigating unmet needs from the patient perspective may address daily difficulties and optimize care. Our aim w...

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs.

The British journal of radiology
OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor prognosis as defined by the need for intensive unit care and mechanical ventilation. We tested the fea...

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.

Chest
BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment.

Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.

International journal of environmental research and public health
The goals of this study were to develop a risk prediction model in unmet dental care needs and to explore the intersection between social determinants of health and unmet dental care needs in the United States. Data from the 2016 Medical Expenditure ...