AIMC Topic: Humans

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Construction of a new smooth support vector machine model and its application in heart disease diagnosis.

PloS one
Support vector machine (SVM) is a new machine learning method developed from statistical learning theory. Since the objective function of the unconstrained SVM model is a non-smooth function, a lot of fast optimization algorithms can't be used to fin...

Video gaming improves robotic surgery simulator success: a multi-clinic study on robotic skills.

Journal of robotic surgery
We aimed to investigate the effects of video game habits, duration of experience, and training in different surgical clinics on the success of robotic surgery simulators. In this prospective, observational, comparative, and multi-clinical study, all ...

Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study.

Endoscopy
BACKGROUND : Deep learning models have previously been established to predict the histopathology and invasion depth of gastric lesions using endoscopic images. This study aimed to establish and validate a deep learning-based clinical decision support...

Visual classification of pressure injury stages for nurses: A deep learning model applying modern convolutional neural networks.

Journal of advanced nursing
AIMS: To develop a deep learning model for pressure injury stages classification based on real-world photographs and compare its performance with that of clinical nurses to seek the opportunity of its application in clinical settings.

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.

JACC. Cardiovascular imaging
BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been ...

Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

Gastrointestinal endoscopy
In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and...

Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis.

Artificial intelligence in medicine
In this paper, we study human-AI collaboration protocols, a design-oriented construct aimed at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We applied this construct in two user studies involving 12 specialist rad...

Development of a deep learning-based tool to assist wound classification.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressur...