AI Medical Compendium Topic:
Cluster Analysis

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Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol.

International journal of environmental research and public health
Predicting crash injury severity is a crucial constituent of reducing the consequences of traffic crashes. This study developed machine learning (ML) models to predict crash injury severity using 15 crash-related parameters. Separate ML models for ea...

COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda.

Respiratory medicine
Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 2030. To better characterize this condition, clinicians have classified patients sharing certain sympto...

Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms.

Frontiers in immunology
Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely studied during the patien...

DCT-MIL: Deep CNN transferred multiple instance learning for COPD identification using CT images.

Physics in medicine and biology
While many pre-defined computed tomographic (CT) measures have been utilized to characterize chronic obstructive pulmonary disease (COPD), it is still challenging to represent pathological alternations of multiple dimensions and highly spatial hetero...

A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis.

PloS one
Medical data are often tricky to get mined for patterns even by the generally demonstrated successful modern methodologies of deep learning. This paper puts forward such a medical classification task, where patient registers of two of the categories ...

Optimization of Skewed Data Using Sampling-Based Preprocessing Approach.

Frontiers in public health
In the past few years, classification has undergone some major evolution. With a constant surge of the amount of data gathered from different sources, efficient processing and analysis of data is becoming difficult. Due to the uneven distribution of ...

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.

Sensors (Basel, Switzerland)
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with breast cancer. More effort is needed to assess the role of these viruses in the detection and diagnosis of breast cancer cases in women. The aim of this paper ...

Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction.

Neural networks : the official journal of the International Neural Network Society
In unsupervised learning, there is no apparent straightforward cost function that can capture the significant factors of variations and similarities. Since natural systems have smooth dynamics, an opportunity is lost if an unsupervised objective func...