Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Dialogue-based simulation is a real-world practice technique for medical and clinical education that...
BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm di...
BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health inform...
Artificial intelligence (AI) software that analyzes medical images is becoming increasingly prevalen...
Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is ...
Visual pattern detection and discrimination are essential first steps for scene analysis. Numerous h...
OBJECTIVE: Recognizing what physicians know and do not know about a particular disease is one of the...
Deep networks provide a potentially rich interconnection between neuroscientific and artificial appr...
Meningioma is the one of the most common type of brain tumor, it as arises from the meninges and enc...
Deep neural networks (DNNs) trained in a supervised way suffer from two known problems. First, the m...
Growth/no growth boundary models for Bacillus spores that accounted for the effects of environmental...
The level set based deformable models (LDM) are commonly used for medical image segmentation. Howeve...
In this paper, we present a novel approach for 3D dental model segmentation via deep Convolutional N...
Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation thera...
 While an explosion in technological sophistication has revolutionized surgery within the operating ...
The Hippocratic oath and the Belmont report articulate foundational principles for how physicians in...
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging...
This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundar...
In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boost...
Vitreomacular adhesion (VMA) represents a prognostic biomarker in the management of exudative macula...
In this paper, synchronization of stochastic reaction-diffusion neural networks with Dirichlet bound...