AIMC Topic: Algorithms

Clear Filters Showing 26021 to 26030 of 28713 articles

Optimizing Equity: Working towards Fair Machine Learning Algorithms in Laboratory Medicine.

The journal of applied laboratory medicine
BACKGROUND: Methods of machine learning provide opportunities to use real-world data to solve complex problems. Applications of these methods in laboratory medicine promise to increase diagnostic accuracy and streamline laboratory operations leading ...

COMBINING HI-RESOLUTION SCAN MODE WITH DEEP LEARNING RECONSTRUCTION ALGORITHMS IN CARDIAC CT.

Radiation protection dosimetry
To investigate the impact of combining the high-resolution (Hi-res) scan mode with deep learning image reconstruction (DLIR) algorithm in CT. Two phantoms (Catphan600® and Lungman, small, medium, large size) were CT scanned using combinations of Hi-r...

Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

Nuclear medicine review. Central & Eastern Europe
BACKGROUND: This study aims to evaluate the performance of a deep learning enhancement method in PET images reconstructed with a shorter acquisition time, and different reconstruction algorithms. The impact of the enhancement on clinical decisions wa...

A densely connected LDCT image denoising network based on dual-edge extraction and multi-scale attention under compound loss.

Journal of X-ray science and technology
BACKGROUND: Low dose computed tomography (LDCT) uses lower radiation dose, but the reconstructed images contain higher noise that can have negative impact in disease diagnosis. Although deep learning with the edge extraction operators reserves edge i...

Traditional and deep learning-oriented medical and biological image analysis.

Bratislavske lekarske listy
We investigated various methods for image segmentation and image processing for the segmentation of MRI of human medical data, as well as bioinformatics for the segmentation of brain cell details, in this work. The goal is to demonstrate and bring va...

Identification of spinal tuberculosis subphenotypes using routine clinical data: a study based on unsupervised machine learning.

Annals of medicine
OBJECTIVE: The identification of spinal tuberculosis subphenotypes is an integral component of precision medicine. However, we lack proper study models to identify subphenotypes in patients with spinal tuberculosis. Here we identified possible subphe...

Classification of Histopathological Images from Breast Cancer Patients Using Deep Learning: A Comparative Analysis.

Critical reviews in biomedical engineering
Cancer, a leading cause of mortality, is distinguished by the multi-stage conversion of healthy cells into cancer cells. Discovery of the disease early can significantly enhance the possibility of survival. Histology is a procedure where the tissue o...

[Age assessment using CT of knee joint and neural network technologies].

Sudebno-meditsinskaia ekspertiza
Age assessment of living persons plays an important role in clinical and sports medicine, as well as in law practice. Traditional methods have a number of problems: age restrictions, technical difficulties of visualization, low reproducibility and su...

Clinical Importance of 3D Volography in Breast Imaging.

Advances in experimental medicine and biology
The clinical applications of the volography algorithm and concomitant refraction-corrected reflection algorithm as described in Chap. 10 are discussed here. Comparisons with an H&E stained image, discussion of glandular tissue visibility, related bio...