AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cluster Analysis

Showing 181 to 190 of 1323 articles

Clear Filters

A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs.

PeerJ
INTRODUCTION: This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension who were treated with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor B (ARB) drugs and to identify key features affecting patient...

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

Revista brasileira de epidemiologia = Brazilian journal of epidemiology
OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in th...

Pseudo-class part prototype networks for interpretable breast cancer classification.

Scientific reports
Interpretability in machine learning has become increasingly important as machine learning is being used in more and more applications, including those with high-stakes consequences such as healthcare where Interpretability has been regarded as a key...

Biomechanical Posture Analysis in Healthy Adults with Machine Learning: Applicability and Reliability.

Sensors (Basel, Switzerland)
Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, whi...

Composite attention mechanism network for deep contrastive multi-view clustering.

Neural networks : the official journal of the International Neural Network Society
Contrastive learning-based deep multi-view clustering methods have become a mainstream solution for unlabeled multi-view data. These methods usually utilize a basic structure that combines autoencoder, contrastive learning, or/and MLP projectors to g...

Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning, and clustering.

Accident; analysis and prevention
Chain reaction crashes (CRC) begin with a two-vehicle collision and rapidly intensify as more vehicles get directly involved. CRCs result in more extensive damage compared to two-vehicle crashes and understanding the progression of a two-vehicle coll...

Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.

The journal of allergy and clinical immunology. In practice
BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes.

An Intuitionistic Fuzzy C-Means and Local Information-Based DCT Filtering for Fast Brain MRI Segmentation.

Journal of imaging informatics in medicine
Structural and photometric anomalies in the brain magnetic resonance images (MRIs) affect the segmentation performance. Moreover, a sudden change in intensity between two boundaries of the brain tissues makes it prone to data uncertainty, resulting i...