AIMC Topic: Algorithms

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Segmentation, feature extraction and classification of leukocytes leveraging neural networks, a comparative study.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The gold standard of leukocyte differentiation is a manual examination of blood smears, which is not only time and labor intensive but also susceptible to human error. As to automatic classification, there is still no comparative study of cell segmen...

Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information.

Journal of structural biology
Efficient and high-accuracy filtering of cryo-electron microscopy (cryo-EM) micrographs is an emerging challenge with the growing speed of data collection and sizes of datasets. Convolutional neural networks (CNNs) are machine learning models that ha...

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

International journal of antimicrobial agents
BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combination has been emphasised. However, antibiotic combination prescribing lacks a rapid identification of feasibility, while its risk of drug interactions is...

Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.

Cell metabolism
The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpreta...

N-Level Hierarchy-Based Optimal Control to Develop Therapeutic Strategies for Ecological Evolutionary Dynamics Systems.

IEEE transactions on neural networks and learning systems
This article mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for ecological evolutionary dynamics systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging...

Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics.

Journal of medical Internet research
Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its g...

An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome.

BMC bioinformatics
BACKGROUND: Predicting outcome of breast cancer is important for selecting appropriate treatments and prolonging the survival periods of patients. Recently, different deep learning-based methods have been carefully designed for cancer outcome predict...

Multi-armed bandits, Thomson sampling and unsupervised machine learning in phylogenetic graph search.

Cladistics : the international journal of the Willi Hennig Society
A phylogenetic graph search relies on a large number of highly parameterized search procedures (e.g. branch-swapping, perturbation, simulated annealing, genetic algorithm). These procedures vary in effectiveness over datasets and at alternative point...

PASTFNet: a paralleled attention spatio-temporal fusion network for micro-expression recognition.

Medical & biological engineering & computing
Micro-expressions (MEs) play such an important role in predicting a person's genuine emotions, as to make micro-expression recognition such an important resea rch focus in recent years. Most recent researchers have made efforts to recognize MEs with ...