Public Health & Policy

Ethics

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

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Deep Learning for Encrypted Traffic Classification and Unknown Data Detection.

Despite the widespread use of encryption techniques to provide confidentiality over Internet communi...

Artificial intelligence and clinical anatomical education: Promises and perils.

Anatomy educators are often at the forefront of adopting innovative and advanced technologies for te...

PINC: A Tool for Non-Coding RNA Identification in Plants Based on an Automated Machine Learning Framework.

There is evidence that non-coding RNAs play significant roles in the regulation of nutrient homeosta...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value t...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making...

Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT.

We describe a protocol to perform fast and non-arbitrary quality control of single-cell RNA sequenci...

Synchronization control of time-delay neural networks via event-triggered non-fragile cost-guaranteed control.

This paper is devoted to event-triggered non-fragile cost-guaranteed synchronization control for tim...

A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT.

OBJECTIVES: Magnetic resonance imaging has high sensitivity in detecting early brainstem infarction ...

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer.

BACKGROUND: Despite the fact that tumor microenvironment (TME) and gene mutations are the main deter...

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment suppo...

A Concise Yet Effective Model for Non-Aligned Incomplete Multi-View and Missing Multi-Label Learning.

In reality, learning from multi-view multi-label data inevitably confronts three challenges: missing...

Deep-TOF-PET: Deep learning-guided generation of time-of-flight from non-TOF brain PET images in the image and projection domains.

We aim to synthesize brain time-of-flight (TOF) PET images/sinograms from their corresponding non-TO...

A novel combined deep learning methodology to non-invasively estimate hemoglobin levels in blood with high accuracy.

Hemoglobin is an essential protein found in blood and should not fall below a certain level in human...

Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques.

BACKGROUND: Lung cancer has the highest mortality rate in the world, twice as high as the second hig...

Low precision decentralized distributed training over IID and non-IID data.

Decentralized distributed learning is the key to enabling large-scale machine learning (training) on...

A unified analysis of convex and non‑convex ‑ball projection problems.

The task of projecting onto norm balls is ubiquitous in statistics and machine learning, yet the av...

Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms.

Anaplastic lymphoma kinase (ALK) and ROS oncogene 1 (ROS1) gene fusions are well-established key pla...

Adsorbate-adsorbent potential energy function from second virial coefficient data: a non-linear Hopfield Neural Network approach.

The Hopfield Neural Network has been successfully applied to solve ill-posed inverse problems in dif...

Deep Learning with Multimodal Integration for Predicting Recurrence in Patients with Non-Small Cell Lung Cancer.

Due to high recurrence rates in patients with non-small cell lung cancer (NSCLC), medical profession...

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