Public Health & Policy

Health Policy

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

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Leveraging data and AI to deliver on the promise of digital health.

Rising rates of NCDs threaten fragile healthcare systems in low- and middle-income countries. Fortun...

A Low-Cost Assistive Robot for Children with Neurodevelopmental Disorders to Aid in Daily Living Activities.

In this paper, we present a new low-cost robotic platform that has been explicitly developed to incr...

Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University.

There is increasing use of psychotherapy apps in mental health care. This mixed methods pilot stud...

Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks.

Continuous and non-invasive respiratory rate (RR) monitoring would significantly improve patient out...

Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation.

Policy Points With increasing integration of artificial intelligence and machine learning in medicin...

Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications.

OBJECTIVE: Quality gaps in medical imaging datasets lead to profound errors in experiments. Our obje...

Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion.

Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the ...

Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization.

The Bayesian method is capable of capturing real-world uncertainties/incompleteness and properly add...

Predicting innovative firms using web mining and deep learning.

Evidence-based STI (science, technology, and innovation) policy making requires accurate indicators ...

Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.

Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop...

E-sensing and nanoscale-sensing devices associated with data processing algorithms applied to food quality control: a systematic review.

Devices of human-based senses such as e-noses, e-tongues and e-eyes can be used to analyze different...

Low-Cost and Device-Free Human Activity Recognition Based on Hierarchical Learning Model.

Human activity recognition (HAR) has been a vital human-computer interaction service in smart homes....

Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients.

BACKGROUND: The clinical impact of postoperative opioid use requires accurate prediction strategies ...

CEFEs: A CNN Explainable Framework for ECG Signals.

In the healthcare domain, trust, confidence, and functional understanding are critical for decision ...

Image Quality Enhancement Using a Deep Neural Network for Plane Wave Medical Ultrasound Imaging.

Plane wave imaging (PWI), a typical ultrafast medical ultrasound imaging mode, adopts single plane w...

Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring.

Approaches to reliably predict the developmental potential of embryos and select suitable embryos fo...

Proposal of a novel Artificial Intelligence Distribution Service platform for healthcare.

In this paper, we focus on presenting a novel AI-based service platform proposal called AIDI (Artifi...

A hybrid deep learning technology for PM air quality forecasting.

The concentration of PM is one of the main factors in evaluating the air quality in environmental sc...

Automating chest radiograph imaging quality control.

PURPOSE: To automate diagnostic chest radiograph imaging quality control (lung inclusion at all four...

Development of a deep learning-based image quality control system to detect and filter out ineligible slit-lamp images: A multicenter study.

BACKGROUND AND OBJECTIVE: Previous studies developed artificial intelligence (AI) diagnostic systems...

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