AI Medical Compendium Topic:
Supervised Machine Learning

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Multi-layer pseudo-supervision for histopathology tissue semantic segmentation using patch-level classification labels.

Medical image analysis
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotations. However, drawing such labels on the giga-pixel whole slide images...

Proactive approach for preamble detection in 5G-NR PRACH using supervised machine learning and ensemble model.

Scientific reports
The physical random access channel (PRACH) is used in the uplink of cellular systems for initial access requests from the users. It is very hard to achieve low latency by implementing conventional methods in 5G. The performance of the system degrades...

Discriminative Mixture Variational Autoencoder for Semisupervised Classification.

IEEE transactions on cybernetics
In this article, a deep probability model, called the discriminative mixture variational autoencoder (DMVAE), is developed for the feature extraction in semisupervised learning. The DMVAE consists of three parts: 1) the encoding; 2) decoding; and 3) ...

Semisupervised Multiple Choice Learning for Ensemble Classification.

IEEE transactions on cybernetics
Ensemble learning has many successful applications because of its effectiveness in boosting the predictive performance of classification models. In this article, we propose a semisupervised multiple choice learning (SemiMCL) approach to jointly train...

Learning From Weakly Labeled Data Based on Manifold Regularized Sparse Model.

IEEE transactions on cybernetics
In multilabel learning, each training example is represented by a single instance, which is relevant to multiple class labels simultaneously. Generally, all relevant labels are considered to be available for labeled data. However, instances with a fu...

Supervised Machine Learning-Based Decision Support for Signal Validation Classification.

Drug safety
INTRODUCTION: Signal validation in pharmacovigilance is the process of evaluating data to decide whether evidence is sufficient to justify further assessment of a detected signal. During the signal validation process, safety experts in our organizati...

WVALE: Weak variational autoencoder for localisation and enhancement of COVID-19 lung infections.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic is a major global health crisis of this century. The use of neural networks with CT imaging can potentially improve clinicians' efficiency in diagnosis. Previous studies in this field have primarily foc...

Exploration of Black Boxes of Supervised Machine Learning Models: A Demonstration on Development of Predictive Heart Risk Score.

Computational intelligence and neuroscience
Machine learning (ML) often provides applicable high-performance models to facilitate decision-makers in various fields. However, this high performance is achieved at the expense of the interpretability of these models, which has been criticized by p...

MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.

Computers in biology and medicine
BACKGROUND: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due t...

What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges.

Sensors (Basel, Switzerland)
From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from smartp...