AI Medical Compendium Topic:
Supervised Machine Learning

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The path to international medals: A supervised machine learning approach to explore the impact of coach-led sport-specific and non-specific practice.

PloS one
Research investigating the nature and scope of developmental participation patterns leading to international senior-level success is mainly explorative up to date. One of the criticisms of earlier research was its typical multiple testing for many in...

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation.

NeuroImage
Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bun...

Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients.

Scientific reports
Intensity harmonization techniques (IHT) are mandatory to homogenize multicentric MRIs before any quantitative analysis because signal intensities (SI) do not have standardized units. Radiomics combine quantification of tumors' radiological phenotype...

Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BMC genomics
BACKGROUND: The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far ...

A Neural Network for Image Anomaly Detection with Deep Pyramidal Representations and Dynamic Routing.

International journal of neural systems
Image anomaly detection is an application-driven problem where the aim is to identify novel samples, which differ significantly from the normal ones. We here propose Pyramidal Image Anomaly DEtector (PIADE), a deep reconstruction-based pyramidal appr...

Cross Lingual Sentiment Analysis: A Clustering-Based Bee Colony Instance Selection and Target-Based Feature Weighting Approach.

Sensors (Basel, Switzerland)
The lack of sentiment resources in poor resource languages poses challenges for the sentiment analysis in which machine learning is involved. Cross-lingual and semi-supervised learning approaches have been deployed to represent the most common ways t...

Learning image features with fewer labels using a semi-supervised deep convolutional network.

Neural networks : the official journal of the International Neural Network Society
Learning feature embeddings for pattern recognition is a relevant task for many applications. Deep learning methods such as convolutional neural networks can be employed for this assignment with different training strategies: leveraging pre-trained m...

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

Genes
The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction ma...

Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?

Sensors (Basel, Switzerland)
Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sens...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

IEEE journal of biomedical and health informatics
Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effecti...