Public Health & Policy

Ethics

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

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ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning.

Protein secretion has a pivotal role in many biological processes and is particularly important for ...

Propensity-Matched Comparison of 90-Day Complications in Robotic-Assisted Versus Non-Robotic Assisted Lumbar Fusion.

STUDY DESIGN: Retrospective single center propensity-matched observational cohort study that include...

DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding.

Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 nucleotides. A growin...

LncRNAWiki 2.0: a knowledgebase of human long non-coding RNAs with enhanced curation model and database system.

LncRNAWiki, a knowledgebase of human long non-coding RNAs (lncRNAs), has been rapidly expanded by in...

Clinical Medical Ethics: How Did We Start? Where Are We Heading?

The author presents his view of the start of clinical medical ethics and ideas on where the broader ...

A machine learning technology to improve the risk of non-invasive prenatal tests.

BACKGROUND: Timely and accurate diagnosis of genetic diseases can lead to proper action and preventi...

On Algorithmic Fairness in Medical Practice.

The application of machine-learning technologies to medical practice promises to enhance the capabil...

A Method for Localizing Non-Reference Sequences to the Human Genome.

As the last decade of human genomics research begins to bear the fruit of advancements in precision ...

Distinguishing Intramedullary Spinal Cord Neoplasms from Non-Neoplastic Conditions by Analyzing the Classic Signs on MRI in the Era of AI.

Intramedullary lesions can be challenging to diagnose, given the wide range of possible pathologies....

Novel artificial intelligence approach for automatic differentiation of fetal occiput anterior and non-occiput anterior positions during labor.

OBJECTIVES: To describe a newly developed machine-learning (ML) algorithm for the automatic recognit...

[Artificial Intelligence in internal medicine : development of a model predicting length of stay for non-elective admissions].

Efficient management of hospitalized patients requires carefully planning each stay by taking into a...

Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed ...

A Cascaded Deep Learning Framework for Detecting Aortic Dissection Using Non-contrast Enhanced Computed Tomography.

Aortic dissection (AD) is a rare but potentially fatal disease with high mortality. The aim of this ...

Non-invasive Detection of Bowel Sounds in Real-life Settings Using Spectrogram Zeros and Autoencoding.

Gastrointestinal (GI) diseases are amongst the most painful and dangerous clinical cases, due to ine...

Transfer learning of CNN-based signal quality assessment from clinical to non-clinical PPG signals.

Photoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to assess blo...

[Let's open the black box: eXplainable Artificial Intelligence (XAI).].

The so-called "opacity" of artificial intelligence (AI), the black box model, raises concerns about ...

End-to-End Non-Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography.

PURPOSE: Clinical TNM staging is a key prognostic factor for patients with lung cancer and is used t...

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