AIMC Topic: Humans

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Machine-learning models for predicting surgical site infections using patient pre-operative risk and surgical procedure factors.

American journal of infection control
BACKGROUND: Surgical site infections (SSIs) are a significant health care problem as they can cause increased medical costs and increased morbidity and mortality. Assessing a patient's preoperative risk factors can improve risk stratification and hel...

Integrating model explanations and hybrid priors into deep stacked networks for the "safe zone" prediction of acetabular cup.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Existing state-of-the-art "safe zone" prediction methods are statistics-based methods, image-matching techniques, and machine learning methods. Yet, those methods bring a tension between accuracy and interpretability.

Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Accurately diagnosing malignant biliary strictures (MBSs) as benign or malignant remains challenging. It has been suggested that direct visualization and interpretation of cholangioscopy images provide greater accuracy for strict...

Inter-Slice Resolution Improvement Using Convolutional Neural Network with Orbital Bone Edge-Aware in Facial CT Images.

Journal of digital imaging
The 3D modeling of orbital bones in facial CT images is essential to provide a customized implant for reconstructions of orbit and related structures during surgery. However, 3D models of the orbital bone show an aliasing effect and disconnected thin...

MRI-Based Artificial Intelligence in Rectal Cancer.

Journal of magnetic resonance imaging : JMRI
Rectal cancer (RC) accounts for approximately one-third of colorectal cancer (CRC), with death rates increasing in patients younger than 50 years old. Magnetic resonance imaging (MRI) is routinely performed for tumor evaluation. However, the semantic...

Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.

Journal of digital imaging
The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had ...

A survey of catheter tracking concepts and methodologies.

Medical image analysis
Catheter tracking has become an integral part of interventional radiology. Over the last decades, researchers have significantly contributed to theoretical and technical catheter tracking solutions. However, most of the published work thus far focuse...

3D vessel-like structure segmentation in medical images by an edge-reinforced network.

Medical image analysis
The vessel-like structure in biomedical images, such as within cerebrovascular and nervous pathologies, is an essential biomarker in understanding diseases' mechanisms and in diagnosing and treating diseases. However, existing vessel-like structure s...

Automatic detection of three cell types in a microscope image based on deep learning.

Journal of biophotonics
With the continuous integration of deep learning and the technique of molecular biology, target detection models must accurately detect the position of each cell in the image and classify it correctly. We present a model for the multi-scale feature f...