Statistical Analysis of Clustering on Breast Cancer Cell Culture Images

Usage of images as sources of information in assays requires a degree of image processing, which can be performed by a hu man observer in the quality of a subjective estimation,or performed by amethod which leverages the intensity values that make up the image and ultimately represent an objective measurement,resulting in the ability to conclude statisticallywhether there is or not a certain characteristic intrinsic to the image. In this work,the application of k-Means is evaluated within an unexplored whole-cell culture perspective to provide new insights on potential large-scale signaling processes.

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Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1109/gmepe/pahce65777.2025.11002838
Primary Topic
AI in cancer detection
Type
article
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article

Statistical Analysis of Clustering on Breast Cancer Cell Culture Images

G.V. Juan Pablo, Angelica Lindlöf, A. Savchenko, Veani Fernando et al.
AI in cancer detection
article

Statistical Analysis of Clustering on Breast Cancer Cell Culture Images

G.V. Juan Pablo, Angelica Lindlöf, A. Savchenko, Veani Fernando, D.I. Maximiliano, H.M. Aseneth
article en

Abstract

Usage of images as sources of information in assays requires a degree of image processing, which can be performed by a hu man observer in the quality of a subjective estimation,or performed by amethod which leverages the intensity values that make up the image and ultimately represent an objective measurement,resulting in the ability to conclude statisticallywhether there is or not a certain characteristic intrinsic to the image. In this work,the application of k-Means is evaluated within an unexplored whole-cell culture perspective to provide new insights on potential large-scale signaling processes.

Gender equality
Openalex Percentile: Top 95%
AI in cancer detection
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