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View article: NOMATTERXAI: Generating “No Matter What” Alterfactual Examples for Explaining Black-Box Text Classification Models
NOMATTERXAI: Generating “No Matter What” Alterfactual Examples for Explaining Black-Box Text Classification Models Open
In Explainable AI (XAI), counterfactual explanations (CEs) are a well-studied method to communicate feature relevance through contrastive reasoning of ``what if'' to explain AI models' predictions. However, they only focus on important (i.…
View article: Unraveling Interwoven Roles of Large Language Models in Authorship Privacy: Obfuscation, Mimicking, and Verification
Unraveling Interwoven Roles of Large Language Models in Authorship Privacy: Obfuscation, Mimicking, and Verification Open
View article: NoMatterXAI: Generating "No Matter What" Alterfactual Examples for Explaining Black-Box Text Classification Models
NoMatterXAI: Generating "No Matter What" Alterfactual Examples for Explaining Black-Box Text Classification Models Open
In Explainable AI (XAI), counterfactual explanations (CEs) are a well-studied method to communicate feature relevance through contrastive reasoning of "what if" to explain AI models' predictions. However, they only focus on important (i.e.…
View article: Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning Open
Several parameter-efficient fine-tuning methods based on adapters have been proposed as a streamlined approach to incorporate not only a single specialized knowledge into existing Pre-Trained Language Models (PLMs) but also multiple of the…
View article: Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers
Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers Open
Existing works show that augmenting the training data of pre-trained language models (PLMs) for classification tasks fine-tuned via parameter-efficient fine-tuning methods (PEFT) using both clean and adversarial examples can enhance their …
View article: Author Correction: Efficient automated error detection in medical data using deep-learning and label-clustering
Author Correction: Efficient automated error detection in medical data using deep-learning and label-clustering Open
View article: #92 : An Artificial Intelligence Algorithm Outperforms Highly Variable Embryologist Grading for Predicting the Likelihood of Pregnancy Outcome from Embryo Images
#92 : An Artificial Intelligence Algorithm Outperforms Highly Variable Embryologist Grading for Predicting the Likelihood of Pregnancy Outcome from Embryo Images Open
Background and Aims: Embryologist evaluation of embryos is critical for ensuring successful pregnancy outcomes. Standard, manual evaluation is variable, subjective, and time-consuming. The aim of this study was to evaluate whether an artif…
View article: #91 : Development of a Combined Artificial Intelligence Score for Evaluating Both Embryo Ploidy and Viability to Aid in Embryo Selection During IVF
#91 : Development of a Combined Artificial Intelligence Score for Evaluating Both Embryo Ploidy and Viability to Aid in Embryo Selection During IVF Open
Background and Aims: Artificial intelligence (AI) is being increasingly used for non-invasive evaluation of embryo quality during IVF. Previous studies described development of AI for selecting embryos likely to be euploid (genetics AI), o…
View article: #316 : Improved Time to Pregnancy When Combining an Artificial Intelligence Score and Morphology Grading for Embryo Selection During IVF
#316 : Improved Time to Pregnancy When Combining an Artificial Intelligence Score and Morphology Grading for Embryo Selection During IVF Open
Background and Aims: Embryo selection is critical in determining IVF success yet continues to be challenging due to the subjectivity of morphology grading methods, especially when grading fair/average quality embryos. Improving embryo sele…
View article: Efficient automated error detection in medical data using deep-learning and label-clustering
Efficient automated error detection in medical data using deep-learning and label-clustering Open
View article: DEVELOPMENT OF A NON-INVASIVE ARTIFICIAL INTELLIGENCE ALGORITHM FOR IDENTIFICATION OF EUPLOID EMBRYOS WITH HIGH MORPHOLOGICAL QUALITY DURING IVF
DEVELOPMENT OF A NON-INVASIVE ARTIFICIAL INTELLIGENCE ALGORITHM FOR IDENTIFICATION OF EUPLOID EMBRYOS WITH HIGH MORPHOLOGICAL QUALITY DURING IVF Open
View article: P-144 An artificial intelligence algorithm demonstrates optimal performance for evaluating embryo genetic status at 120 hours post-fertilization
P-144 An artificial intelligence algorithm demonstrates optimal performance for evaluating embryo genetic status at 120 hours post-fertilization Open
Study question What is the effect of time-point on performance of a non-invasive artificial intelligence (AI) algorithm for evaluating embryo genetic status? Summary answer While predictive ability was maintained across different time-poin…
View article: Efficient automated error detection in medical data using deep-learning and label-clustering
Efficient automated error detection in medical data using deep-learning and label-clustering Open
Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual info…
View article: Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF
Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF Open
STUDY QUESTION Can an artificial intelligence (AI) model predict human embryo ploidy status using static images captured by optical light microscopy? SUMMARY ANSWER Results demonstrated predictive accuracy for embryo euploidy and showed a …
View article: A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data
A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data Open
Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centrali…
View article: Automated detection of poor-quality data: case studies in healthcare
Automated detection of poor-quality data: case studies in healthcare Open
View article: IDENTIFYING INHERENT POOR QUALITY EMBRYO DATA USING ARTIFICIAL INTELLIGENCE TO IMPROVE AI PERFORMANCE AND CLINICAL REPORTING
IDENTIFYING INHERENT POOR QUALITY EMBRYO DATA USING ARTIFICIAL INTELLIGENCE TO IMPROVE AI PERFORMANCE AND CLINICAL REPORTING Open
View article: Machine learning approaches to physical activity prediction in young children using accelerometer data
Machine learning approaches to physical activity prediction in young children using accelerometer data Open
Early childhood development is arguably the most significant period in the course of life. It is widely recognized that physical activity (PA) during early childhood plays an influential role on current and future developments of the child…
View article: The employees’ perceptions of mindfulness and meditation regarding work performance: The case of staff members in KMS Technology Corporation
The employees’ perceptions of mindfulness and meditation regarding work performance: The case of staff members in KMS Technology Corporation Open
Objectives: The main purpose of this study is to answer the question whether mindfulness meditation training should be implemented in the workplace. In order to provide profound solutions to the inquiry, the thesis attempts to first identi…
View article: Educator engagement and interaction and children's physical activity in early childhood education and care settings: an observational study protocol
Educator engagement and interaction and children's physical activity in early childhood education and care settings: an observational study protocol Open
Introduction The benefits of regular physical activity for children are significant. Previous research has addressed the quantity and quality of children's physical activity while in early childhood education and care (ECEC) settings, yet …