The interpretability of the activity signal detection model for wood-boring pests Semanotus bifasciatus in the larval stage.
Sign Up to like & getrecommendations! Published in 2023 at "Pest management science"
DOI: 10.1002/ps.7566
Abstract: BACKGROUND The acoustic detection model of activity signals based on deep learning could detect wood-boring pests accurately and reliably. However, the black-box characteristics of the deep learning model limited the credibility of the results and… read more here.
Keywords: interpretability; activity; model; detection model ... See more keywords
Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit
Sign Up to like & getrecommendations! Published in 2021 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2021.103876
Abstract: Interpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation… read more here.
Keywords: learning models; patients admitted; deep learning; attention ... See more keywords
An evolving neuro-fuzzy system based on uni-nullneurons with advanced interpretability capabilities
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.04.065
Abstract: Abstract This paper proposes a hybrid architecture based on neural networks, fuzzy systems, and n-uninorms for solving pattern classification problems, termed as ENFS-Uni0 (short for evolving neuro-fuzzy system based on uni-nullneurons). The model can produce… read more here.
Keywords: neuro fuzzy; fuzzy system; uni nullneurons; system based ... See more keywords
Imparting interpretability to word embeddings while preserving semantic structure
Sign Up to like & getrecommendations! Published in 2020 at "Natural Language Engineering"
DOI: 10.1017/s1351324920000315
Abstract: Abstract As a ubiquitous method in natural language processing, word embeddings are extensively employed to map semantic properties of words into a dense vector representation. They capture semantic and syntactic relations among words, but the… read more here.
Keywords: imparting interpretability; interpretability word; embeddings preserving; interpretability ... See more keywords
Seeking a better balance between efficiency and interpretability: Comparing the likert response format with the Guttman response format.
Sign Up to like & getrecommendations! Published in 2022 at "Psychological methods"
DOI: 10.1037/met0000462
Abstract: The Likert item response format for items is almost ubiquitous in the social sciences and has particular virtues regarding the relative simplicity of item-generation and the efficiency for coding responses. However, in this article, we… read more here.
Keywords: interpretability; format; guttman response; efficiency ... See more keywords
Improving drug-drug interactions prediction with interpretability via meta-path-based information fusion
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad041
Abstract: Drug-drug interactions (DDIs) are compound effects when patients take two or more drugs at the same time, which may weaken the efficacy of drugs or cause unexpected side effects. Thus, accurately predicting DDIs is of… read more here.
Keywords: information; interpretability; semantics; meta path ... See more keywords
Precision oncology: a review to assess interpretability in several explainable methods.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad200
Abstract: Great efforts have been made to develop precision medicine-based treatments using machine learning. In this field, where the goal is to provide the optimal treatment for each patient based on his/her medical history and genomic… read more here.
Keywords: interpretability; oncology; review; machine learning ... See more keywords
Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3049569
Abstract: Building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of… read more here.
Keywords: integer weighted; interpretability; machine; weighted clauses ... See more keywords
Toward Practical Usage of the Attention Mechanism as a Tool for Interpretability
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3169772
Abstract: Natural language processing (NLP) has been one of the subfields of artificial intelligence much affected by the recent neural revolution. Architectures such as recurrent neural networks (RNNs) and attention-based transformers helped propel the state of… read more here.
Keywords: interpretability; attention mechanism; attention weights; toward practical ... See more keywords
Interpretability and Repeatability of Radiomic Features: Applied on In Vivo Tumor Models
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3269101
Abstract: Radiomic features are typically used in machine learning models and are proven to generate reliable results when predicting tumor grade and responses to treatment. However, the inherent non-biological-interpretability of the radiomic features strongly hinders their… read more here.
Keywords: interpretability; tumor models; repeatability radiomic; tumor ... See more keywords
Graph Node Based Interpretability Guided Sample Selection for Active Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3215017
Abstract: While supervised learning techniques have demonstrated state-of-the-art performance in many medical image analysis tasks, the role of sample selection is important. Selecting the most informative samples contributes to the system attaining optimum performance with minimum… read more here.
Keywords: active learning; interpretability; sample selection; sample ... See more keywords