Public Health & Policy

Ethics

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

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Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model.

BACKGROUND AND OBJECTIVE: Currently, it is challenging to detect acute ischemic stroke (AIS)-related...

MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomas.

Twelve to 66% of patients with clinically non-functioning pituitary adenoma (NFPA) experience tumor ...

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, th...

CAS: corpus of clinical cases in French.

BACKGROUND: Textual corpora are extremely important for various NLP applications as they provide inf...

Deep learning for cerebral angiography segmentation from non-contrast computed tomography.

Cerebral computed tomography angiography is a widely available imaging technique that helps in the d...

lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.

Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex ...

A machine learning approach for mortality prediction only using non-invasive parameters.

At present, the traditional scoring methods generally utilize laboratory measurements to predict mor...

A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. ...

The ethics of AI in health care: A mapping review.

This article presents a mapping review of the literature concerning the ethics of artificial intelli...

A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.

The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produc...

Non-ischemic endocardial scar geometric remodeling toward topological machine learning.

Scar tissues have been important factors in determining the progression of myocardial diseases and t...

Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study.

Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. Howeve...

Improving disaggregation models of malaria incidence by ensembling non-linear models of prevalence.

Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable r...

Artificial Intelligence and Robotics in Nursing: Ethics of Caring as a Guide to Dividing Tasks Between AI and Humans.

Nurses have traditionally been regarded as clinicians that deliver compassionate, safe, and empathet...

Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury.

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of s...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall surv...

What is the optimal surveillance strategy for non-dysplastic Barrett's esophagus?

PURPOSE OF REVIEW: There is conflicting data on the effectiveness of the currently recommended endos...

Pinning bipartite synchronization for inertial coupled delayed neural networks with signed digraph via non-reduced order method.

The study investigates bipartite synchronization of inertial coupled delayed neural networks (ICDNNs...

Effects of non-facilitated meaningful activities for people with dementia in long-term care facilities: A systematic review.

This systematic review sought to evaluate the effectiveness of non-facilitated meaningful activities...

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