AIMC Topic: Health Care Costs

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Machine learning outperforms clinical experts in classification of hip fractures.

Scientific reports Feb 8, 2022
Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population ageing, the number of incident hip fractures is predicted to increase globally. As fracture classificat...
Health Care Costs Hip Fractures Hip Joint Machine Learning Humans Radiography
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Deep learning for prediction of population health costs.

BMC medical informatics and decision making Feb 3, 2022
BACKGROUND: Accurate prediction of healthcare costs is important for optimally managing health costs. However, methods leveraging the medical richness from data such as health insurance claims or electronic health records are missing.
Humans Neural Networks, Computer Germany Health Care Costs Insurance Claim Review Deep Learning Population Health
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Machine learning versus regression modelling in predicting individual healthcare costs from a representative sample of the nationwide claims database in France.

The European journal of health economics : HEPAC : health economics in prevention and care Aug 9, 2021
BACKGROUND: Innovative provider payment methods that avoid adverse selection and reward performance require accurate prediction of healthcare costs based on individual risk adjustment. Our objective was to compare the performances of a simple neural ...
Linear Models Health Care Costs Machine Learning Databases, Factual Health Services Humans
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A machine learning approach to predict healthcare cost of breast cancer patients.

Scientific reports Jun 14, 2021
This paper presents a novel machine learning approach to perform an early prediction of the healthcare cost of breast cancer patients. The learning phase of our prediction method considers the following two steps: (1) in the first step, the patients ...
Markov Chains Models, Economic Health Care Costs Breast Neoplasms Cluster Analysis Humans Electronic Health Records Female Machine Learning
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Design Comorbidity Portfolios to Improve Treatment Cost Prediction of Asthma Using Machine Learning.

IEEE journal of biomedical and health informatics Jun 3, 2021
Comorbidity is an important factor to consider when trying to predict the cost of treating asthma patients. When an asthmatic patient suffered from comorbidity, the cost of treating such a patient becomes dependent on the nature of the comorbidity. T...
Machine Learning Asthma Comorbidity Humans Neural Networks, Computer Health Care Costs
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Artificial intelligence (AI) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. A comprehensive review.

Diagnostic pathology Mar 17, 2021
BACKGROUND: The role of Artificial intelligence (AI) which is defined as the ability of computers to perform tasks that normally require human intelligence is constantly expanding. Medicine was slow to embrace AI. However, the role of AI in medicine ...
Attitude to Computers Health Care Costs Pathology Image Interpretation, Computer-Assisted Practice Patterns, Physicians' Health Knowledge, Attitudes, Practice Predictive Value of Tests Microscopy Cost-Benefit Analysis Pathologists Artificial Intelligence Reproducibility of Results Attitude of Health Personnel Humans
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Improving Global Healthcare and Reducing Costs Using Second-Generation Artificial Intelligence-Based Digital Pills: A Market Disruptor.

International journal of environmental research and public health Jan 19, 2021
Improving global health requires making current and future drugs more effective and affordable. While healthcare systems around the world are faced with increasing costs, branded and generic drug companies are facing the challenge of creating market...
Delivery of Health Care Health Facilities Quality of Health Care Health Care Costs Telemedicine Humans Artificial Intelligence Drugs, Generic
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Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Oct 12, 2020
OBJECTIVES: Traditional risk scores improved the definition of the initial therapeutic strategy in acute coronary syndrome (ACS), but they were not designed for predicting long-term individual risks and costs. In parallel, attempts to directly predic...
Cost Savings Acute Coronary Syndrome Health Care Costs Humans Machine Learning Female Male Treatment Outcome Morbidity Risk Factors Aged
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Learning hidden patterns from patient multivariate time series data using convolutional neural networks: A case study of healthcare cost prediction.

Journal of biomedical informatics Sep 25, 2020
OBJECTIVE: To develop an effective and scalable individual-level patient cost prediction method by automatically learning hidden temporal patterns from multivariate time series data in patient insurance claims using a convolutional neural network (CN...
Cohort Studies Health Care Costs Humans Neural Networks, Computer
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Feature Selection for Health Care Costs Prediction Using Weighted Evidential Regression.

Sensors (Basel, Switzerland) Aug 6, 2020
Although many authors have highlighted the importance of predicting people's health costs to improve healthcare budget management, most of them do not address the frequent need to know the reasons behind this prediction, i.e., knowing the factors tha...
Male Cluster Analysis Health Care Costs Algorithms Humans Female Neural Networks, Computer
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