Abstract: In today’s modern Internet era, botnets have become one of the primary cybersecurity threats, capable of causing immense disruption, financial losses, and data breaches. Botnets exist in ...
Abstract: Dempster–Shafer (DS) evidence theory provides a powerful framework for modeling uncertainty, reasoning, and combining information from multiple sources. However, it may yield ...
A hybrid optimizer that combines information-theoretic entropy minimization, Bayesian variational updates, and hierarchical clustering to achieve ultra-fast, deterministic convergence on black-box ...
A hierarchical clustering approach to dissect behavioral symptoms in early-stage breast cancer (BC).
Autoimmune conditions and ‘breast implant illness’ in breast cancer patients with implant-based breast reconstructions. Proportions of patients with clinically meaningful symptoms by CL at Y1 (may not ...
Acoustic cluster therapy combined with chemotherapy showed a 29% tumor diameter reduction, compared to 7% with chemotherapy alone in colorectal liver metastases. The therapy uses PS101, activated by ...
BACKGROUND Leprosy, a neglected tropical disease caused by Mycobacterium leprae, presents significant public health challenges in Brazil due to its slow progression, dermato-neurological ...
Objective Systemic lupus erythematosus (SLE), a systemic autoimmune disease with heterogeneous severity, poses a challenge in classifying patients due to its dynamic phenotype. We therefore aimed to ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
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