Public Health & Policy

Ethics

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

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DeepRA: A novel deep learning-read-across framework and its application in non-sugar sweeteners mutagenicity prediction.

Non-sugar sweeteners (NSSs) or artificial sweeteners have long been used as food chemicals since Wor...

Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks.

Non-small cell lung carcinoma (NSCLC) is the most common type of pulmonary cancer, one of the deadli...

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prost...

Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.

In the food industry, the increasing use of automatic processes in the production line is contributi...

Christian anthropology-based contributions to the ethics of socially assistive robots in care for older adults.

Our society, in general, and health care, in particular, faces notable challenges due to the emergen...

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell ...

Take five? A coherentist argument why medical AI does not require a new ethical principle.

With the growing application of machine learning models in medicine, principlist bioethics has been ...

Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.

BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbi...

Predicting Lymphovascular Invasion in Non-small Cell Lung Cancer Using Deep Convolutional Neural Networks on Preoperative Chest CT.

RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatmen...

Deep learning-based low-dose CT simulator for non-linear reconstruction methods.

BACKGROUND: Computer algorithms that simulate lower-doses computed tomography (CT) images from clini...

Synergistic Machine Learning Accelerated Discovery of Nanoporous Inorganic Crystals as Non-Absorbable Oral Drugs.

Machine learning (ML) has taken drug discovery to new heights, where effective ML training requires ...

An interpretable ensemble structure with a non-iterative training algorithm to improve the predictive accuracy of healthcare data analysis.

The modern development of healthcare is characterized by a set of large volumes of tabular data for ...

Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion for Undersampled MRI Reconstruction.

Magnetic resonance imaging is subject to slow acquisition times due to the inherent limitations in d...

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms.

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid sc...

Artificial Intelligence in Otolaryngology: Topics in Epistemology & Ethics.

To fuel artificial intelligence (AI) potential in clinical practice in otolaryngology, researchers m...

New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.

BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical ...

Systematic literature review on reinforcement learning in non-communicable disease interventions.

There is evidence that reducing modifiable risk factors and strengthening medical and health interve...

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