AIMC Topic: Algorithms

Clear Filters Showing 1021 to 1030 of 28713 articles

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.

Scientific reports
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...

Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network.

Scientific reports
Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with subtle early symptoms leading to delayed diagnosis. Ferroptosis, a cell death process associated with iron metabolism dysregulation, has been linked t...

Predictive Modeling of Osteonecrosis of the Femoral Head Progression Using MobileNetV3_Large and Long Short-Term Memory Network: Novel Approach.

JMIR medical informatics
BACKGROUND: The assessment of osteonecrosis of the femoral head (ONFH) often presents challenges in accuracy and efficiency. Traditional methods rely on imaging studies and clinical judgment, prompting the need for advanced approaches. This study aim...

Artificial intelligence algorithms for differentiating pseudoprogression from true progression in high-grade gliomas: A systematic review and meta-analysis.

Neurosurgical review
Differentiating pseudoprogression (PsP) from true progression (TP) in high-grade glioma (HGG) patients is still challenging and critical for effective treatment management. This meta-analysis evaluates the diagnostic accuracy of artificial intelligen...

Targeting neurodegeneration: three machine learning methods for G9a inhibitors discovery using PubChem and scikit-learn.

Journal of computer-aided molecular design
In light of the increasing interest in G9a's role in neuroscience, three machine learning (ML) models, that are time efficient and cost effective, were developed to support researchers in this area. The models are based on data provided by PubChem an...

Semi-supervised medical image segmentation based on multi-stage iterative training and high-confidence pseudo-labeling.

Biomedical physics & engineering express
Due to the scarcity and high cost of pixel-level annotations for training data, semi-supervised learning has gradually become a key solution. Most existing methods rely on consistency regularization and pseudo-label generation, often adopting multi-b...

An improved domain-adversarial network for predicting hemodialysis adequacy.

Biomedical physics & engineering express
Hemodialysis (HD) is the primary life-sustaining treatment for patients with end-stage renal disease (ESRD). However, current real-time monitoring methods during dialysis are costly, complex, and not widely adopted. Therefore, this study aims to prop...

PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.

PloS one
Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative technology with applications spanning robotics, virtual reality, medicine, and rehabilitation. However, existing BCI frameworks face several limitati...

MSMCE: A novel representation module for classification of raw mass spectrometry data.

PloS one
Mass spectrometry (MS) analysis plays a crucial role in the biomedical field; however, the high dimensionality and complexity of MS data pose significant challenges for feature extraction and classification. Deep learning has become a dominant approa...

Bag-of-words is competitive with sum-of-embeddings language-inspired representations on protein inference.

PloS one
Inferring protein function is a fundamental and long-standing problem in biology. Laboratory experiments in this field are often expensive, and therefore large-scale computational protein inference from readily available amino acid sequences is neede...