Public Health & Policy

Ethics

Latest AI and machine learning research in ethics for healthcare professionals.

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Showing 1156-1176 of 2,859 articles
Physics guided neural networks for modelling of non-linear dynamics.

The success of the current wave of artificial intelligence can be partly attributed to deep neural n...

Mean-square stabilization of impulsive neural networks with mixed delays by non-fragile feedback involving random uncertainties.

In this paper, we consider a class of neural networks with mixed delays and impulsive interferences....

Comparison of Two-Port and Three-Port Approaches in Robotic Lobectomy for Non-Small Cell Lung Cancer.

BACKGROUND: Robot-assisted lobectomy has been used to treat non-small cell lung cancer and usually u...

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such ...

Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected a...

Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review.

BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development...

Deep Learning-Based Non-Intrusive Commercial Load Monitoring.

Commercial load is an essential demand-side resource. Monitoring commercial loads helps not only com...

Non-Deep Active Learning for Deep Neural Networks.

One way to improve annotation efficiency is active learning. The goal of active learning is to selec...

Non-iterative learning machine for identifying CoViD19 using chest X-ray images.

CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around ...

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were use...

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and h...

Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models.

AIMS: This study aims to predict poor glycemic control during Ramadan among non-fasting patients wit...

Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.

Causal discovery from observational data is a fundamental problem in science. Though the linear non-...

Two stream Non-Local CNN-LSTM network for the auxiliary assessment of mental retardation.

At present, the assessment of mental retardation is mainly based on clinical interview, which requir...

Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management.

Studies on the ethics of automating clinical or research decision making using artificial intelligen...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Artificial intelligence techniques were explored to assess the ability to anticipate self-harming be...

Measuring ethical behavior with AI and natural language processing to assess business success.

Everybody claims to be ethical. However, there is a huge difference between declaring ethical behavi...

Disturbance Observer-Based Minimum Entropy Control for a Class of Disturbed Non-Gaussian Stochastic Systems.

In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems ...

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes resear...

A non-destructive methodology for determination of cantaloupe sugar content using machine vision and deep learning.

BACKGROUND: To determine the maturity of cantaloupe, measuring the soluble solid content (SSC) as th...

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