Results 71 to 80 of about 1,249,172 (345)

On Discrimination Discovery and Removal in Ranked Data using Causal Graph

, 2018
Predictive models learned from historical data are widely used to help companies and organizations make decisions. However, they may digitally unfairly treat unwanted groups, raising concerns about fairness and discrimination. In this paper, we study the
Andersen M S, Avin Chen, Bhattacharyya A., Bradley Ralph Allan, Calmon Flavio, Kalisch Markus, Kamiran Faisal, Nabi Razieh, Zhang Lu   +8 more
core   +1 more source

Whole‐Blood RNA Sequencing Profiling of Patients With Rheumatoid Arthritis Treated With Tofacitinib

ACR Open Rheumatology, EarlyView.
Objective Patients with rheumatoid arthritis (RA) often fail to respond to therapies, including JAK inhibitors (JAKi), and treatment allocation is made via a trial‐and‐error strategy. A comprehensive analysis of responses to JAKi, including tofacitinib, by RNA sequencing (RNAseq) would allow the discovery of transcriptomic markers with a two‐fold ...
Chiara Bellocchi, Ennio Giulio Favalli, Gabriella Maioli, Elena Agape, Marzia Rossato, Matteo Paini, Adriana Severino, Barbara Vigone, Martina Biggioggero, Elena Trombetta, Roberto Caporali, Lorenzo Beretta   +11 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

Deep Learning-Based Standard Sign Language Discrimination

IEEE Access, 2023
General sign language recognition models are only designed for recognizing categories, i.e., such models do not discriminate standard and nonstandard sign language actions made by learners.
Menglin Zhang, Shuying Yang, Min Zhao
doaj   +1 more source

Achieving non-discrimination in prediction [PDF]

arXiv, 2017
Discrimination-aware classification is receiving an increasing attention in data science fields. The pre-process methods for constructing a discrimination-free classifier first remove discrimination from the training data, and then learn the classifier from the cleaned data.
arxiv  

CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging [PDF]

arXiv, 2022
Recently, self-supervised instance discrimination methods have achieved significant success in learning visual representations from unlabeled photographic images. However, given the marked differences between photographic and medical images, the efficacy of instance-based objectives, focusing on learning the most discriminative global features in the ...
arxiv  

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source

Analysis Dictionary Learning: An Efficient and Discriminative Solution [PDF]

arXiv, 2019
Discriminative Dictionary Learning (DL) methods have been widely advocated for image classification problems. To further sharpen their discriminative capabilities, most state-of-the-art DL methods have additional constraints included in the learning stages. These various constraints, however, lead to additional computational complexity.
arxiv  

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

Advanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source