Public Health & Policy

Ethics

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

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Evaluation of hypoxia-inducible factor-1α and urine non-transferrin-bound iron concentrations in cats with chronic kidney disease.

INTRODUCTION: Hypoxia-inducible factors (HIF) regulate gene transcription, which aids hypoxia adapta...

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, ...

Radiomics and deep learning features of pericoronary adipose tissue on non-contrast computerized tomography for predicting non-calcified plaques.

BACKGROUND: Inflammation of coronary arterial plaque is considered a key factor in the development o...

Combination Therapy with Baricitinib and Narrowband Ultraviolet B for Active Non-Segmental Vitiligo: A Retrospective Controlled Study.

BACKGROUND: Vitiligo is a chronic autoimmune disease manifested by depigmented patches of skin devoi...

A non-local dual-stream fusion network for laryngoscope recognition.

PURPOSE: To use deep learning technology to design and implement a model that can automatically clas...

Passivity and robust passivity of inertial memristive neural networks with time-varying delays via non-reduced order method.

This study examines the concepts of passivity and robust passivity in inertial memristive neural net...

Ethical and Bias Considerations in Artificial Intelligence/Machine Learning.

As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications...

Assessment of body composition and prediction of infectious pancreatic necrosis via non-contrast CT radiomics and deep learning.

AIM: The current study aims to delineate subcutaneous adipose tissue (SAT), visceral adipose tissue ...

Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans.

Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understandin...

A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulat...

Machine Learning Guided Rational Design of a Non-Heme Iron-Based Lysine Dioxygenase Improves its Total Turnover Number.

Highly selective C-H functionalization remains an ongoing challenge in organic synthetic methodologi...

Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.

BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long duration...

AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease Using Novel Non-Invasive Biomarkers.

Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting ...

Diagnostic Performance of Artificial Intelligence-Based Angiography-Derived Non-Hyperemic Pressure Ratio Using Pressure Wire as Reference.

BACKGROUND: The angiography-derived non-hyperemic pressure ratio (angioNHPR) is a novel index of NHP...

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