Nature

Classification using hierarchical clustering of tumor-infiltrating immune cells identifies poor prognostic ovarian cancers with high levels of COX expression

Ovarian cancer is the leading cause of death in gynecological malignancies. The majority of patients with ovarian cancer are identified at advanced stages of the disease and eventually die of disease ...
clinicaladvisor.com

Clinical Clustering May Improve Diagnosis and Treatment of Pediatric Behçet Disease

Researchers identified 7 distinct phenotypic clusters among pediatric patients with Behçet disease, with manifestations varying based on geography and system involvement. Findings from an ...
InfoWorld

Machine learning: Clustering and classification on the campaign trail

As the election season rampages on, we categorize voters into broad demographics — soccer moms, NASCAR dads, blacks, whites, ALICEs, yuppies — in an attempt to understand and discuss this complex, ...
JSTOR Daily

A Comparison of a Discriminant versus a Clustering Analysis of a Patient Classification for Chronic Disease Care

Medical Care, Vol. 12, No. 11 (Nov., 1974), pp. 944-957 (14 pages) Discrimination analysis has been used to assess the value of a Patient Classification Questionnaire in assigning patients to an ...
Visual Studio Magazine

Clustering Non-Numeric Data Using Python

Clustering data is the process of grouping items so that items in a group (cluster) are similar and items in different groups are dissimilar. After data has been clustered, the results can be analyzed ...
InfoWorld

Deep learning vs. machine learning: Understand the differences

A classification problem is a supervised learning problem that asks for a choice between two or more classes, usually providing probabilities for each class. Leaving out neural networks and deep ...