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Medical Ethics / Professional Responsibility

Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.

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Robot Assisted Surgical Ward Rounds: Virtually Always There.

 While an explosion in technological sophistication has revolutionized surgery within the operating ...

Effective Pneumothorax Detection for Chest X-Ray Images Using Local Binary Pattern and Support Vector Machine.

Automatic image segmentation and feature analysis can assist doctors in the treatment and diagnosis ...

Protecting Your Patients' Interests in the Era of Big Data, Artificial Intelligence, and Predictive Analytics.

The Hippocratic oath and the Belmont report articulate foundational principles for how physicians in...

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging...

Breast lesion classification based on supersonic shear-wave elastography and automated lesion segmentation from B-mode ultrasound images.

Supersonic shear-wave elastography (SWE) has emerged as a useful imaging modality for breast lesion ...

A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.

This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundar...

Melanoma segmentation based on deep learning.

Malignant melanoma is one of the most deadly forms of skin cancer, which is one of the world's faste...

Post-boosting of classification boundary for imbalanced data using geometric mean.

In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boost...

Evaluating the impact of vitreomacular adhesion on anti-VEGF therapy for retinal vein occlusion using machine learning.

Vitreomacular adhesion (VMA) represents a prognostic biomarker in the management of exudative macula...

Synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded delays.

In this paper, synchronization of stochastic reaction-diffusion neural networks with Dirichlet bound...

Fuzzy spectral clustering for automated delineation of chronic wound region using digital images.

Chronic wound is an abnormal disease condition of localized injury to the skin and its underlying ti...

Synchronization of Reaction-Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays.

This paper is concerned with synchronization for a class of reaction-diffusion neural networks with ...

A Novel Ensemble Method for Imbalanced Data Learning: Bagging of Extrapolation-SMOTE SVM.

Class imbalance ubiquitously exists in real life, which has attracted much interest from various dom...

TED: A Tolerant Edit Distance for segmentation evaluation.

In this paper, we present a novel error measure to compare a computer-generated segmentation of imag...

Characterizing Architectural Distortion in Mammograms by Linear Saliency.

Architectural distortion (AD) is a common cause of false-negatives in mammograms. This lesion usuall...

Robust differential expression analysis by learning discriminant boundary in multi-dimensional space of statistical attributes.

BACKGROUND: Performing statistical tests is an important step in analyzing genome-wide datasets for ...

Conceptual Design and Procedure for an Autonomous Intramyocardial Injection Catheter.

This article discusses existing catheter systems and proposes a conceptual design and procedure for ...

DOOB-MARTIN COMPACTIFICATION OF A MARKOV CHAIN FOR GROWING RANDOM WORDS SEQUENTIALLY.

We consider a Markov chain that iteratively generates a sequence of random finite words in such a wa...

Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative i...

Pancreas Segmentation in MRI using Graph-Based Decision Fusion on Convolutional Neural Networks.

Automated pancreas segmentation in medical images is a prerequisite for many clinical applications, ...

Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using ...

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