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Cluster Analysis

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Application of Semi-supervised Fuzzy Clustering Based on Knowledge Weighting and Cluster Center Learning to Mammary Molybdenum Target Image Segmentation.

Interdisciplinary sciences, computational life sciences
Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large,...

Statistical and machine learning methods for immunoprofiling based on single-cell data.

Human vaccines & immunotherapeutics
Immunoprofiling has become a crucial tool for understanding the complex interactions between the immune system and diseases or interventions, such as therapies and vaccinations. Immune response biomarkers are critical for understanding those relation...

Packets-to-Prediction: An Unobtrusive Mechanism for Identifying Coarse-Grained Sleep Patterns with WiFi MAC Layer Traffic.

Sensors (Basel, Switzerland)
A good night's sleep is of the utmost importance for the seamless execution of our cognitive capabilities. Unfortunately, the research shows that one-third of the US adult population is severely sleep deprived. With college students as our focused gr...

Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention.

IEEE transactions on bio-medical engineering
OBJECTIVE: Heart failure, respiratory failure and kidney failure are three severe organ failures (OF) that have high mortalities and are most prevalent in intensive care units. The objective of this work is to offer insights into OF clustering from t...

Active learning for prediction of tensile properties for material extrusion additive manufacturing.

Scientific reports
Machine learning techniques were used to predict tensile properties of material extrusion-based additively manufactured parts made with Technomelt PA 6910, a hot melt adhesive. An adaptive data generation technique, specifically an active learning pr...

Deep audio embeddings for vocalisation clustering.

PloS one
The study of non-human animals' communication systems generally relies on the transcription of vocal sequences using a finite set of discrete units. This set is referred to as a vocal repertoire, which is specific to a species or a sub-group of a spe...

ABTCN: an efficient hybrid deep learning approach for atmospheric temperature prediction.

Environmental science and pollution research international
Temperature prediction is an important and significant step for monitoring global warming and the environment to save and protect human lives. The climatology parameters such as temperature, pressure, and wind speed are time-series data and are well ...

Multi-population Black Hole Algorithm for the problem of data clustering.

PloS one
The retrieval of important information from a dataset requires applying a special data mining technique known as data clustering (DC). DC classifies similar objects into a groups of similar characteristics. Clustering involves grouping the data aroun...

TCGAN: Convolutional Generative Adversarial Network for time series classification and clustering.

Neural networks : the official journal of the International Neural Network Society
Recent works have demonstrated the superiority of supervised Convolutional Neural Networks (CNNs) in learning hierarchical representations from time series data for successful classification. These methods require sufficiently large labeled data for ...