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Supervised Machine Learning

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Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Medical image analysis
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, developing an automated system for nodule segmentation can enhance user...

Weakly supervised nuclei segmentation based on pseudo label correction and uncertainty denoising.

Artificial intelligence in medicine
Nuclei segmentation plays a vital role in computer-aided histopathology image analysis. Numerous fully supervised learning approaches exhibit amazing performance relying on pathological image with precisely annotations. Whereas, it is difficult and t...

Utilizing semantically enhanced self-supervised graph convolution and multi-head attention fusion for herb recommendation.

Artificial intelligence in medicine
Traditional Chinese herbal medicine has long been recognized as an effective natural therapy. Recently, the development of recommendation systems for herbs has garnered widespread academic attention, as these systems significantly impact the applicat...

Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Computers in biology and medicine
Chemical graphs are mathematical representations of molecular structures, where atoms are represented as vertices, while chemical bonds are depicted as edges of a graph. The chemical graphs are widely used in cheminformatics to analyze molecular prop...

Diverse Teacher-Students for deep safe semi-supervised learning under class mismatch.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised learning can significantly boost model performance by leveraging unlabeled data, particularly when labeled data is scarce. However, real-world unlabeled data often contain unseen-class samples, which can hinder the classification of s...

The optimization and impact of public sports service quality based on the supervised learning model and artificial intelligence.

Scientific reports
Aiming at the optimization of public sports service quality, this study analyzes the public sports service data deeply by constructing a supervised learning model. Firstly, the theoretical framework of this study is established. Secondly, the technic...

A novel self-supervised graph clustering method with reliable semi-supervision.

Neural networks : the official journal of the International Neural Network Society
Cluster analysis, as a core technique in unsupervised learning, has widespread applications. With the increasing complexity of data, deep clustering, which integrates the advantages of deep learning and traditional clustering algorithms, demonstrates...

Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...

Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10-Year Retrospective Study.

Journal of veterinary internal medicine
BACKGROUND: Bovine leukemia virus (BLV) infection in beef cattle has received less attention than in dairy herds, despite its potential impact on the beef industry.