AIMC Journal:
Computer methods and programs in biomedicine

Showing 251 to 260 of 844 articles

Precise angle estimation of capsule robot in ultrasound using heatmap guided two-stage network.

Computer methods and programs in biomedicine
PURPOSE: A capsule robot can be controlled inside gastrointestinal (GI) tract by an external permanent magnet outside of human body for finishing non-invasive diagnosis and treatment. Locomotion control of capsule robot relies on the precise angle fe...

Optimal machine learning methods for prediction of high-flow nasal cannula outcomes using image features from electrical impedance tomography.

Computer methods and programs in biomedicine
BACKGROUND: High-flow nasal cannula (HNFC) is able to provide ventilation support for patients with hypoxic respiratory failure. Early prediction of HFNC outcome is warranted, since failure of HFNC might delay intubation and increase mortality rate. ...

Medical image super-resolution reconstruction algorithms based on deep learning: A survey.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: With the high-resolution (HR) requirements of medical images in clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution (LR) medical images have become a research hotspot. This type of meth...

Deep learning-based assessment of knee septic arthritis using transformer features in sonographic modalities.

Computer methods and programs in biomedicine
PURPOSE: Septic arthritis is an infectious disease. Conventionally, the diagnosis of septic arthritis can only be based on the identification of causal pathogens taken from synovial fluid, synovium or blood samples. However, the cultures require seve...

Automated inter-patient arrhythmia classification with dual attention neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Arrhythmia classification based on electrocardiograms (ECG) can enhance clinical diagnostic efficiency. However, due to the significant differences in the number of different categories of heartbeats, the performance of cla...

Relating process and outcome metrics for meaningful and interpretable cannulation skill assessment: A machine learning paradigm.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The quality of healthcare delivery depends directly on the skills of clinicians. For patients on hemodialysis, medical errors or injuries caused during cannulation can lead to adverse outcomes, including potential death. To...

Lightweight multi-scale classification of chest radiographs via size-specific batch normalization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Convolutional neural networks are widely used to detect radiological findings in chest radiographs. Standard architectures are optimized for images of relatively small size (for example, 224 × 224 pixels), which suffices for...

From local counterfactuals to global feature importance: efficient, robust, and model-agnostic explanations for brain connectivity networks.

Computer methods and programs in biomedicine
BACKGROUND: Explainable artificial intelligence (XAI) is a technology that can enhance trust in mental state classifications by providing explanations for the reasoning behind artificial intelligence (AI) models outputs, especially for high-dimension...

A survey on agents applications in healthcare: Opportunities, challenges and trends.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The agent abstraction is a powerful one, developed decades ago to represent crucial aspects of artificial intelligence research. The meaning has transformed over the years and now there are different nuances across research ...

Multi-event survival analysis through dynamic multi-modal learning for ICU mortality prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Survival analysis is widely applied for assessing the expected duration of patient status towards event occurrences such as mortality in healthcare domain, which is generally considered as a time-to-event problem. Patients w...