AIMC Topic: Algorithms

Clear Filters Showing 7551 to 7560 of 28713 articles

Enhancing Classification Accuracy with Integrated Contextual Gate Network: Deep Learning Approach for Functional Near-Infrared Spectroscopy Brain-Computer Interface Application.

Sensors (Basel, Switzerland)
Brain-computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike trad...

Machine learning based DNA melt curve profiling enables automated novel genotype detection.

BMC bioinformatics
Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening f...

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization.

Scientific reports
A prompt diagnosis of breast cancer in its earliest phases is necessary for effective treatment. While Computer-Aided Diagnosis systems play a crucial role in automated mammography image processing, interpretation, grading, and early detection of bre...

Fine tuning deep learning models for breast tumor classification.

Scientific reports
This paper proposes an approach to enhance the differentiation task between benign and malignant Breast TumorsĀ (BT) using histopathology images from the BreakHis dataset. The main stages involve preprocessing, which encompasses image resizing, data p...

Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma.

Scientific reports
Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time...

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpret...

Machine learning and multi-omics data reveal driver gene-based molecular subtypes in hepatocellular carcinoma for precision treatment.

PLoS computational biology
The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratifying highly heterogeneous HCC into molecular subtypes with similar features is crucial for personalized anti-tumor therapies. Although driver genes pla...

Branched Convolutional Neural Networks for Receiver Channel Recovery in High-Frame-Rate Sparse-Array Ultrasound Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
For high-frame-rate ultrasound imaging, it remains challenging to implement on compact systems as a sparse imaging configuration with limited array channels. One key issue is that the resulting image quality is known to be mediocre not only because u...

Machine learning algorithms for identifying contralateral central lymph node metastasis in unilateral cN0 papillary thyroid cancer.

Frontiers in endocrinology
PURPOSE: The incidence of thyroid cancer is growing fast and surgery is the most significant treatment of it. For patients with unilateral cN0 papillary thyroid cancer whether to dissect contralateral central lymph node is still under debating. Here,...

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation-A Systematic Review.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used ...