Results 91 to 100 of about 98,421 (281)

Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

, 2020
Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) architecture to generate synthetic samples for variable length, multi-feature ...
Ger, Stephanie, Klabjan, Diego
core  

A Hybrid Approach Handling Imbalanced Datasets [PDF]

, 2009
Several binary classification problems exhibit imbalance in class distribution, influencing system learning. Indeed, traditional machine learning algorithms are biased towards the majority class, thus producing poor predictive accuracy over the minority one. To overcome this limitation, many approaches have been proposed up to now to build artificially
openaire   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento, Daniela F. Santos, Tuane C. R. G. Vieira, Tiago F. Outeiro   +3 more
wiley   +1 more source

Anomaly Detection Model for Imbalanced Datasets

, 2020
This paper proposes a method to detect bank frauds using a mixed approach combining a stochastic intensity model with the probability of fraud observed on transactions. It is a dynamic unsupervised approach which is able to predict financial frauds. The fraud prediction probability on the financial transaction is derived as a function of the dynamic ...
Houssou, Régis, Robert-Nicoud, Stephan
openaire   +3 more sources

MYCOPHENOLATE MOFETIL TREATMENT REDUCES THE RISK OF TREATMENT ESCALATION DUE TO VASCULAR COMPLICATIONS IN LIMITED CUTANEOUS SYSTEMIC SCLEROSIS: EMULATION OF A TARGET TRIAL FROM ITALIAN RHEUMATOLOGY SOCIETY SPRING REGISTRY

Arthritis Care &Research, Accepted Article.
Objective Mycophenolate Mofetil (MMF) use in limited cutaneous systemic sclerosis (lcSSc) is relatively uncommon due to the lower fibrotic burden and the predominance of the vascular complications. In vitro observations and clinical data from transplanted patients suggest a protective effect of MMF on endothelial function.
Enrico De Lorenzis, Gerlando Natalello, Rossella De Angelis, Lucrezia Verardi, Dilia Giuggioli, Gianluigi Bajocchi, Lorenzo Dagna, Silvia Bellando‐Randone, Giovanni Zanframundo, Rosario Foti, Fabio Cacciapaglia, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Gemma Lepri, Francesco Girelli, Valeria Riccieri, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Pettiti, Alessandra Della Rossa, Maurizio Caminiti, Annamaria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Maria Ilenia De Andres, Alessandro Giollo, Cosimo Bruni, Martina Orlandi, Marco Fornaro, Marta Saracco, Cecilia Agnes, Pier Giacomo Cerasuolo, Gabriella Alonzi, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Corrado Campochiaro, Giacomo De Luca, Veronica Codullo, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria‐Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Fabrizio Conti, Serena Guiducci, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Maria Antonietta D'Agostino, Clodoveo Ferri, Marco Matucci Cerinic, Silvia Laura Bosello, on behalf of SPRING collaborators   +77 more
wiley   +1 more source

A Hybrid Sampling SVM Approach to Imbalanced Data Classification

Abstract and Applied Analysis, 2014
Imbalanced datasets are frequently found in many real applications. Resampling is one of the effective solutions due to generating a relatively balanced class distribution.
Qiang Wang
doaj   +1 more source

Posterior Re-calibration for Imbalanced Datasets

, 2020
Accepted to NeurIPS ...
Tian, Junjiao, Liu, Yen-Cheng, Glaser, Nathan, Hsu, Yen-Chang, Kira, Zsolt   +4 more
openaire   +2 more sources

Moderators of the effects of exercise and manual therapy for people with knee and hip osteoarthritis: A secondary analysis of the MOA trial

Arthritis Care &Research, Accepted Article.
Objective This study aimed to investigate potential moderators influencing the effects of manual therapy and exercise therapy on pain and functional outcomes in individuals with knee and/or hip osteoarthritis, using data from the MOA trial. Design This is a secondary analysis of data from the MOA trial that compared the clinical effectiveness of manual
Daniel Cury Ribeiro, Sarah E. Lamb, J. Haxby Abbott   +2 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification

Applied Artificial Intelligence
Imbalanced class distributions pose a prevalent challenge in numerous classification problems, requiring effective strategies for learning from such skewed data.
Vaibhavi Patel, Hetal Bhavsar
doaj   +1 more source