AIMC Topic: Algorithms

Clear Filters Showing 9361 to 9370 of 28713 articles

Artificial Intelligence-Based Tool for Tumor Detection and Quantitative Tissue Analysis in Colorectal Specimens.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Digital pathology adoption allows for applying computational algorithms to routine pathology tasks. Our study aimed to develop a clinical-grade artificial intelligence (AI) tool for precise multiclass tissue segmentation in colorectal specimens (rese...

Orthodontic craniofacial pattern diagnosis: cephalometric geometry and machine learning.

Medical & biological engineering & computing
Efficient and reliable diagnosis of craniofacial patterns is critical to orthodontic treatment. Although machine learning (ML) is time-saving and high-precision, prior knowledge should validate its reliability. This study proposed a craniofacial ML d...

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed.

Journal of environmental management
Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Mac...

Is deeper always better? Evaluating deep learning models for yield forecasting with small data.

Environmental monitoring and assessment
Predicting crop yields, and especially anomalously low yields, is of special importance for food insecure countries. In this study, we investigate a flexible deep learning approach to forecast crop yield at the provincial administrative level based o...

Structure-based prediction of nucleic acid binding residues by merging deep learning- and template-based approaches.

PLoS computational biology
Accurate prediction of nucleic binding residues is essential for the understanding of transcription and translation processes. Integration of feature- and template-based strategies could improve the prediction of these key residues in proteins. Never...

Graph Neural Networks With Multiple Prior Knowledge for Multi-Omics Data Analysis.

IEEE journal of biomedical and health informatics
With the development of biotechnology, a large amount of multi-omics data have been collected for precision medicine. There exists multiple graph-based prior biological knowledge about omics data, such as gene-gene interaction networks. Recently, the...

Coot-Lion optimized deep learning algorithm for COVID-19 point mutation rate prediction using genome sequences.

Computer methods in biomechanics and biomedical engineering
In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed usin...

Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis.

Neurocritical care
Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary method to predict DCI, but it has low accuracy. This study assessed whether other machine learning (ML) m...

Soft computing applications in the field of human factors and ergonomics: A review of the past decade of research.

Applied ergonomics
The main objectives of this study were to 1) review the literature on the applications of soft computing concepts to the field of human factors and ergonomics (HFE) between 2013 and 2022 and 2) highlight future developments and trends. Multiple soft ...

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time thro...