Nature

Attention-based hybrid contrastive learning for unsupervised person re-identification

Unsupervised person Re-identification (Re-ID) is a challenging task that involves matching pedestrian images from various camera viewpoints without the need for labeled data. This task has acquired ...
Nature

Adaptive clustering for medical image analysis using the improved separation index

The exponential growth of biomedical data—from multi-modal medical images to high-throughput omics profiles—has intensified the need for unsupervised learning methods capable of extracting meaningful ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly heterogeneous presentations and prognoses, as in chronic lymphocytic lymphoma (CLL ...
PBS

Unsupervised Learning #6

We’re moving on from artificial intelligence that needs training labels. We’re moving on from artificial intelligence that needs training labels, called Supervised Learning, to Unsupervised Learning ...
Medical Xpress

Cluster analysis may identify abusive head trauma in children

(HealthDay)—Cluster analysis applied to data from children hospitalized with acute neurologic injury supports the current paradigm that physicians use to diagnose abusive head trauma, according to a ...