| Unsupervised Learning Model | Applications in 5G | Adoption in healthcare delivery | References |
1 | K-means Clustering, Gaussian Mixture Model (GMM), and Expectation Maximization (EM) | In automobile networks, cooperative spectrum sensing, and relay node selection are used. | Medical experts employ these models to develop more intelligent medical decision support systems, particularly for the treatment of liver diseases. | [35] [37] |
2 | Hierarchical Clustering | Detection of anomalies, faults, and intrusions in mobile wireless networks. | To discover the phylogenetic tree of animal evolution, this model can be used in conjunction with DNA sequencing. This is frequently crucial in determining the origin of a viral or disease outbreak. | [24] [35] |
3 | Unsupervised Soft-Clustering ML Framework | In heterogeneous cellular networks, latency is reduced by grouping fog nodes to automatically identify which low-power node (LPN) is converted to a high-power node (HPN). (LPN) is upgraded to a high-power node (HPN) | These models can be used to improve machine learning algorithms’ ability to diagnose chronic diseases. | [35] [38] |
4 | Affinity Propagation Clustering | Data-Driven Resource Management for Ultra-Dense Small Cells | This model can be adopted to investigate important genes associated with ovarian cancer. | [37] |