AIMC Topic: Cluster Analysis

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Artificial intelligence clustering of adult spinal deformity sagittal plane morphology predicts surgical characteristics, alignment, and outcomes.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: AI algorithms have shown promise in medical image analysis. Previous studies of ASD clusters have analyzed alignment metrics-this study sought to complement these efforts by analyzing images of sagittal anatomical spinopelvic landmarks. We h...

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data.

International journal of molecular sciences
High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as mole...

Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network.

Biomolecules
Network-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze...

Protein Complexes Detection Based on Semi-Supervised Network Embedding Model.

IEEE/ACM transactions on computational biology and bioinformatics
A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protein-protein interactions (PPI) network, it is critical but non-trivial to detect protein complexes, th...

FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space.

Molecules (Basel, Switzerland)
The question of molecular similarity is core in cheminformatics and is usually assessed via a comparison based on vectors of properties or molecular fingerprints. We recently exploited variational autoencoders to embed 6M molecules in a chemical spa...

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...

A clustering-based adaptive Neighborhood Retrieval Visualizer.

Neural networks : the official journal of the International Neural Network Society
We introduce a novel adaptive version of the Neighborhood Retrieval Visualizer (NeRV). We maintain the advantages of the conventional NeRV method, while proposing an improvement of the data samples' neighborhood width calculation, in the input and ou...

An Intuitionistic Fuzzy Clustering Approach for Detection of Abnormal Regions in Mammogram Images.

Journal of digital imaging
Breast cancer is one of the leading causes of mortality in the world and it occurs in high frequency among women that carries away many lives. To detect cancer, extraction or segmentation of lesions/tumors is required. Segmentation process is very cr...

Integrated multi-omics analysis of ovarian cancer using variational autoencoders.

Scientific reports
Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi-omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountab...

An Inception Convolutional Autoencoder Model for Chinese Healthcare Question Clustering.

IEEE transactions on cybernetics
Healthcare question answering (HQA) system plays a vital role in encouraging patients to inquire for professional consultation. However, there are some challenging factors in learning and representing the question corpus of HQA datasets, such as high...