Public Health & Policy

Health Policy

Latest AI and machine learning research in health policy for healthcare professionals.

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Automated phenotyping of mild cognitive impairment and Alzheimer's disease and related dementias using electronic health records.

OBJECTIVES: Unstructured and structured data in electronic health records (EHR) are a rich source of...

Extreme Weather, Vulnerable Populations, and Mental Health: The Timely Role of AI Interventions.

Environmental disasters are becoming increasingly frequent and severe, disproportionately impacting ...

Optimizing Diabetic Retinopathy Screening at Primary Health Centres in India: A Cost-Effectiveness Analysis.

BACKGROUND: The eye care package under the Ayushman Bharat comprehensive primary healthcare programm...

Children on wheels: Identifying crash determinants using cluster correspondence analysis.

Child bicyclists (14 years old and younger) are among the most vulnerable road users, facing signifi...

MISTIC: a novel approach for metastasis classification in Italian electronic health records using transformers.

BACKGROUND: Analysis of Electronic Health Records (EHRs) is crucial in real-world evidence (RWE), es...

Image quality improvement in head and neck angiography based on dual-energy CT and deep learning.

OBJECTIVE: Compare the image quality of image reconstructed using deep learning-based image reconstr...

Low-cost algorithms for clinical notes phenotype classification to enhance epidemiological surveillance: A case study.

OBJECTIVE: Our study aims to enhance epidemic intelligence through event-based surveillance in an em...

The present and future of cardiological telemonitoring in Europe: a statement from seven European countries.

Cardiovascular diseases remain one of the leading causes of death worldwide, placing a significant b...

Mother: a maternal online technology for health care dataset.

OBJECTIVES: These data enable the development of both textual and speech based conversational machin...

Improving image quality on pediatric and neonatal radiography using AI-based compensation for image degradation.

PURPOSE: To evaluate the impact of an AI-based, noise reduction technique for compensation of image ...

Assessing the impact of traffic restriction interventions on school air quality: a citizen science-based modelling study.

Air pollution poses a significant threat to human health, especially for the vulnerable groups such ...

Phantom-based evaluation of image quality in Transformer-enhanced 2048-matrix CT imaging at low and ultralow doses.

PURPOSE: To compare the quality of standard 512-matrix, standard 1024-matrix, and Swin2SR-based 2048...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Early diagnosis and access to resources, support and therapy are critical for improving long-term ou...

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis.

BACKGROUND: Cancer survivors and their caregivers, particularly those from disadvantaged backgrounds...

Insight into endophytic microbiota-driven geographical and bioactive signatures toward a novel quality assessment model for Codonopsis Radix.

Codonopsis Radix, a medicinal and dietary herb in traditional Chinese medicine, largely owes its pha...

Implementation of a national AI technology program on cardiovascular outcomes and the health system.

Coronary artery disease (CAD) is a major cause of ill health and death worldwide. Coronary computed ...

Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data.

Over 2 billion people worldwide are impacted by the global dilemma of access to clean and safe drink...

Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.

Recent advances in deep learning models have transformed medical imaging analysis, particularly in r...

Label-Free Medical Image Quality Evaluation by Semantics-Aware Contrastive Learning in IoMT.

With the rapid development of the Internet-of-Medical-Things (IoMT) in recent years, it has emerged ...

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