AIMC Topic: Cluster Analysis

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Segmentation of acetowhite region in uterine cervical image based on deep learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Acetowhite (AW) region is a critical physiological phenomenon of precancerous lesions of cervical cancer. An accurate segmentation of the AW region can provide a useful diagnostic tool for gynecologic oncologists in screening cervical can...

Fully unsupervised deep mode of action learning for phenotyping high-content cellular images.

Bioinformatics (Oxford, England)
MOTIVATION: The identification and discovery of phenotypes from high content screening images is a challenging task. Earlier works use image analysis pipelines to extract biological features, supervised training methods or generate features with neur...

Novel strategy for applying hierarchical density-based spatial clustering of applications with noise towards spectroscopic analysis and detection of melanocytic lesions.

Melanoma research
Advancements in dermoscopy techniques have elucidated identifiable characteristics of melanoma which revolve around the asymmetrical constitution of melanocytic lesions consequent of unfettered proliferative growth as a malignant lesion. This study e...

XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data.

Briefings in bioinformatics
The lack of explainability is one of the most prominent disadvantages of deep learning applications in omics. This 'black box' problem can undermine the credibility and limit the practical implementation of biomedical deep learning models. Here we pr...

Phenotypic Characterization of Chronic Kidney Patients Through Hierarchical Clustering.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Chronic kidney disease is a major public health problem around the world and this disease early diagnosis is still a great challenge as it is asymptomatic in its early stages. Thus, in order to identify variables capable of assisting CKD diagnosis an...

Developing and testing an automated qualitative assistant (AQUA) to support qualitative analysis.

Family medicine and community health
Qualitative research remains underused, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those burdens, and has been used in exploratory studies to reduce t...

Statistical Inference for Clustering Results Interpretation in Clinical Practice.

Studies in health technology and informatics
The relevance of this study lies in improvement of machine learning models understanding. We present a method for interpreting clustering results and apply it to the case of clinical pathways modeling. This method is based on statistical inference an...

Improved FCM algorithm for fisheye image cluster analysis for tree height calculation.

Mathematical biosciences and engineering : MBE
The height of standing trees is an important index in forestry research. This index is not only hard to measure directly but also the environmental factors increase the measurement difficulty. Therefore, the measurement of the height of standing tree...

Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Briefings in bioinformatics
Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discrimina...

Deep embedded clustering with multiple objectives on scRNA-seq data.

Briefings in bioinformatics
In recent years, single-cell RNA sequencing (scRNA-seq) technologies have been widely adopted to interrogate gene expression of individual cells; it brings opportunities to understand the underlying processes in a high-throughput manner. Deep embedde...