Health Policy

Economics of AI and human task sharing for decision making in screening mammography.

The rising global incidence of breast cancer and the persistent shortage of specialized radiologists have heightened the demand for innovative solutions in mammography screening. Artificial intelligence (AI) has emerged as a promising tool to bridge this demand-supply gap, with potential applications ranging from full automation to integrated AI-human decision-making. This study evaluates the econ...

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP) algorithm to extract social determinants of health (SDOH) from free-text notes and quantify the association of SDOH with access to the transplant wa...

Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis.

INTRODUCTION: Maternal mortality refers to a mother's death owing to complications arising from childbirth or pregnancy. This issue is a forefront pub...

Health Communication on the Internet: Promoting Public Health and Exploring Disparities in the Generative AI Era.

Health communication and promotion on the internet have evolved over time, driven by the development of new technologies, including generative artific...

Advanced deep learning models for predicting elemental concentrations in iron ore mine using XRF data: a cost-effective alternative to ICP-MS methods.

Accurate elemental analysis is a critical requirement for mineral exploration, particularly in regions like Iran, where the mining sector has experien...

Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning.

The healthcare industry, aided by technology, leverages the Internet of Things (IoT) paradigm to offer patient/user-related services that are ubiquito...

Communication-Efficient Hybrid Federated Learning for E-Health With Horizontal and Vertical Data Partitioning.

Electronic healthcare (e-health) allows smart devices and medical institutions to collaboratively collect patients' data, which is trained by artifici...

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence.

The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy,...

Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data.

Epidemiologists often handle large datasets with numerous variables and are currently seeing a growing wealth of techniques for data analysis, such as...

Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alt...

Role of artificial intelligence in data-centric additive manufacturing processes for biomedical applications.

The role of additive manufacturing (AM) for healthcare applications is growing, particularly in the aspiration to meet subject-specific requirements. ...

Association of High-Deductible Health Plans and Complicated Appendicitis Among Children.

OBJECTIVE: To determine whether high-deductible health plans (HDHPs) are associated with complicated disease and hospitalization costs for children wi...

End-User Confidence in Artificial Intelligence-Based Predictions Applied to Biomedical Data.

Applications of Artificial Intelligence (AI) are revolutionizing biomedical research and healthcare by offering data-driven predictions that assist in...

Generalizable deep neural networks for image quality classification of cervical images.

Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of i...

Artificial Intelligence (AI) - Powered Documentation Systems in Healthcare: A Systematic Review.

Artificial Intelligence (AI) driven documentation systems are positioned to enhance documentation efficiency and reduce documentation burden in the he...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from Africa...

DeepSeek in Healthcare: Revealing Opportunities and Steering Challenges of a New Open-Source Artificial Intelligence Frontier.

Generative Artificial Intelligence (GAI) has driven several advancements in healthcare, with large language models (LLMs) such as OpenAI's ChatGPT, Go...

Social Determinants and Health Equity Activities: Are They Connected with the Adaptation of AI and Telehealth Services in the U.S. Hospitals?

In recent decades, technological shifts within the healthcare sector have significantly transformed healthcare management and utilization, introducing...

Artificial intelligence and science of patient input: a perspective from people with multiple sclerosis.

Artificial intelligence (AI) can play a vital role in achieving a shift towards predictive, preventive, and personalized medicine, provided we are gui...

Managerial myopia and its barrier to green innovation in high-pollution enterprises: A machine learning approach.

Green technology innovation has become a vital remedy in response to the world's growing ecological problems and the urgent need for sustainable devel...