Public Health & Policy

Ethics

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

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Ethical Considerations in the Use of Artificial Intelligence in Pain Medicine.

Although the integration of artificial intelligence (AI) into medicine and healthcare holds transfor...

Anti-ceramide antibody and sphingosine-1-phosphate as potential biomarkers of unresectable non-small cell lung cancer.

OBJECTIVES: Spingosine-1-phosphate (S1P) and ceramides are bioactive sphingolipids that influence ca...

Retrospective analysis of amantadine response and predictive factors in intensive care unit patients with non-traumatic disorders of consciousness.

BACKGROUND: Disorders of consciousness (DoC) in non-traumatic ICU-patients are often treated with am...

Machine learning techniques for non-destructive estimation of plum fruit weight.

Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yie...

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.

Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium...

Multi-view clustering based on feature selection and semi-non-negative anchor graph factorization.

Multi-view clustering has garnered significant attention due to its capacity to utilize information ...

Mind the Gap: A Neural Network Framework for Imputing Genotypes in Non-Model Species.

Reduced representation sequencing (RRS) has proven to be a cost-effective solution for sequencing su...

Explainable Machine Learning to Predict Treatment Response in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Immune checkpoint inhibitors (ICIs) have demonstrated promise in the treatment of various c...

Bias in adjudication: Investigating the impact of artificial intelligence, media, financial and legal institutions in pursuit of social justice.

The latest global progress report highlights numerous challenges in achieving justice goals, with bi...

A novel non-invasive murine model for rapidly testing drug activity via inhalation administration against .

The efficacy of many compounds against is often limited when administered via conventional oral or ...

Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension.

OBJECTIVE: Congenital heart disease with pulmonary arterial hypertension (CHD-PAH), caused by CHD, i...

Non-stationary Domain Generalization: Theory and Algorithm.

Although recent advances in machine learning have shown its success to learn from independent and id...

Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets.

Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlyi...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet...

π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.

Peptide sequencing via tandem mass spectrometry (MS/MS) is essential in proteomics. Unlike tradition...

Multi-Modal Federated Learning for Cancer Staging Over Non-IID Datasets With Unbalanced Modalities.

The use of machine learning (ML) for cancer staging through medical image analysis has gained substa...

Unsupervised Non-Rigid Histological Image Registration Guided by Keypoint Correspondences Based on Learnable Deep Features With Iterative Training.

Histological image registration is a fundamental task in histological image analysis. It is challeng...

Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning.

Moyamoya disease (MMD) is a progressive cerebrovascular disorder that increases the risk of intracra...

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