AIMC Topic: Cluster Analysis

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spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics.

GigaScience
BACKGROUND: Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly wh...

Policy Library Redundancy Analysis Using K-means Clustering.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This capstone project investigates the application of artificial intelligence (AI) techniques, specifically sentence embedding and k-means clustering using large language models, to address the challenge of policy library redundancy within a healthca...

Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Graph-based deep learning has shown great promise in cancer histopathology image analysis by contextualizing complex morphology and structure across whole slide images to make high quality downstream outcome predictions (ex: prognostication). These m...

Deep learning based decision tree ensembles for incomplete medical datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to ...

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq)...

scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning.

Briefings in bioinformatics
Annotation of cell-types is a critical step in the analysis of single-cell RNA sequencing (scRNA-seq) data that allows the study of heterogeneity across multiple cell populations. Currently, this is most commonly done using unsupervised clustering al...

iDeLUCS: a deep learning interactive tool for alignment-free clustering of DNA sequences.

Bioinformatics (Oxford, England)
SUMMARY: We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic ...

Identification of Sleep Patterns via Clustering of Hypnodensities.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep patterns vary widely between individuals. We explore methods for identifying populations exhibiting similar sleep patterns in an automated fashion using polysomnography data. Our novel approach applies unsupervised machine learning algorithms t...

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991)
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode im...

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances in multimodal single-cell omics technologies enable multiple modalities of molecular attributes, such as gene expression, chromatin accessibility, and protein abundance, to be profiled simultaneously at a global level in i...