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TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification.

Neural networks : the official journal of the International Neural Network Society
Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challenging task due to a variety of issues, such as color inconsistency that results from the non-uniform manual staining operations, clustering of nuclei,...

Effective Transfer Learning with Label-Based Discriminative Feature Learning.

Sensors (Basel, Switzerland)
The performance of natural language processing with a transfer learning methodology has improved by applying pre-training language models to downstream tasks with a large number of general data. However, because the data used in pre-training are irre...

PathDetect-SOM: A Neural Network Approach for the Identification of Pathways in Ligand Binding Simulations.

Journal of chemical theory and computation
Understanding the process of ligand-protein recognition is important to unveil biological mechanisms and to guide drug discovery and design. Enhanced-sampling molecular dynamics is now routinely used to simulate the ligand binding process, resulting ...

An Online Weighted Bayesian Fuzzy Clustering Method for Large Medical Data Sets.

Computational intelligence and neuroscience
With the rapid development of artificial intelligence, various medical devices and wearable devices have emerged, enabling people to collect various health data of themselves in hospitals or other places. This has led to a substantial increase in the...

Word Embedding and Clustering for Patient-Centered Redesign of Appointment Scheduling in Ambulatory Care Settings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
. A key to a more efficient scheduling systems is to ensure appointments are designed to meet patient's needs and to design and simplify appointment scheduling less prone to error. Electronic Health Records (EHR) consist of valuable information about...

Hyperspectral Image Labeling and Classification Using an Ensemble Semi-Supervised Machine Learning Approach.

Sensors (Basel, Switzerland)
Hyperspectral remote sensing has tremendous potential for monitoring land cover and water bodies from the rich spatial and spectral information contained in the images. It is a time and resource consuming task to obtain groundtruth data for these ima...

Optimization of fuzzy c-means (FCM) clustering in cytology image segmentation using the gray wolf algorithm.

BMC molecular and cell biology
BACKGROUND: Image segmentation is considered an important step in image processing. Fuzzy c-means clustering is one of the common methods of image segmentation. However, this method suffers from drawbacks, such as sensitivity to initial values, entra...

The Construction of Online Course Learning Model of Piano Education from the Perspective of Deep Learning.

Computational intelligence and neuroscience
This exploration aims at solving multiple teaching problems in piano online education course. On the premise of collaborative filtering, the K-means clustering algorithm is employed to apply the time data to the neural collaborative filtering algorit...

Dynamic Heterogeneous User Generated Contents-Driven Relation Assessment via Graph Representation Learning.

Sensors (Basel, Switzerland)
Cross-domain decision-making systems are suffering a huge challenge with the rapidly emerging uneven quality of user-generated data, which poses a heavy responsibility to online platforms. Current content analysis methods primarily concentrate on non...

Comparing Sampling Strategies for Tackling Imbalanced Data in Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) using wearable sensors is an increasingly active research topic in machine learning, aided in part by the ready availability of detailed motion capture data from smartphones, fitness trackers, and smartwatches. The go...