AIMC Topic: Algorithms

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Using machine learning to predict outcomes of patients with blunt traumatic aortic injuries.

The journal of trauma and acute care surgery
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...

The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country.

Clinical radiology
AIM: We aimed to investigate the efficiency and accuracy of an artificial intelligence (AI) algorithm for detecting interval cancers in a middle-income country's national screening program.

Comparison of natural language processing algorithms in assessing the importance of head computed tomography reports written in Japanese.

Japanese journal of radiology
PURPOSE: To propose a five-point scale for radiology report importance called Report Importance Category (RIC) and to compare the performance of natural language processing (NLP) algorithms in assessing RIC using head computed tomography (CT) reports...

Multi-scale nested UNet with transformer for colorectal polyp segmentation.

Journal of applied clinical medical physics
BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network based convolutional neural networks have achieved remarkable segmentation performance for biomedical images, but lack of long-range dependencies modelin...

A natural language processing algorithm accurately classifies steatotic liver disease pathology to estimate the risk of cirrhosis.

Hepatology communications
BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunction-associated steatotic liver disease (MASLD). The feasibility of studying MASLD progression in electronic medical records based on histological featur...

1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.

Medicina (Kaunas, Lithuania)
: Patients presenting with ST Elevation Myocardial Infarction (STEMI) due to occlusive coronary arteries remain at a higher risk of excess morbidity and mortality despite being treated with primary percutaneous coronary intervention (PPCI). Identifyi...

Wearable Movement Exploration Device with Machine Learning Algorithm for Screening and Tracking Diabetic Neuropathy-A Cross-Sectional, Diagnostic, Comparative Study.

Biosensors
BACKGROUND: Diabetic neuropathy is one of the most common complications of diabetes mellitus. The aim of this study is to evaluate the Moveo device, a novel device that uses a machine learning (ML) algorithm to detect and track diabetic neuropathy. T...

Introducing surgical intelligence in gynecology: Automated identification of key steps in hysterectomy.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: The analysis of surgical videos using artificial intelligence holds great promise for the future of surgery by facilitating the development of surgical best practices, identifying key pitfalls, enhancing situational awareness, and dissemin...

Observer-based resilient dissipativity control for discrete-time memristor-based neural networks with unbounded or bounded time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This work focuses on the issue of observer-based resilient dissipativity control of discrete-time memristor-based neural networks (DTMBNNs) with unbounded or bounded time-varying delays. Firstly, the Luenberger observer is designed, and additionally ...

A Dual Robust Graph Neural Network Against Graph Adversarial Attacks.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have gained widespread usage and achieved remarkable success in various real-world applications. Nevertheless, recent studies reveal the vulnerability of GNNs to graph adversarial attacks that fool them by modifying graph...