Results 131 to 140 of about 88,634 (286)
Interpretable Diagnostics with SHAP-Rule: Fuzzy Linguistic Explanations from SHAP Values
MathematicsThis study introduces SHAP-Rule, a novel explainable artificial intelligence method that integrates Shapley additive explanations with fuzzy logic to automatically generate interpretable linguistic IF-THEN rules for diagnostic tasks. Unlike purely numeric SHAP vectors, which are difficult for decision-makers to interpret, SHAP-Rule translates feature ...
Alexandra I. Khalyasmaa +2 more
openaire +1 more source
Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis
Advanced Intelligent Systems, EarlyView.A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang +3 more
wiley +1 more source
Machine Learning Accelerates Crystallization for Structure Determination
Angewandte Chemie, EarlyView.Single‐crystal X‐ray diffraction (SCXRD) is often constrained by the difficulty of obtaining suitable crystals. Here, a machine learning‐accelerated co‐crystal discovery workflow is established for a crystalline mate strategy that achieves over 95% prediction accuracy and experimentally delivers 114 co‐crystals from 120 candidates.
Cui‐Zhou Luan +10 more
wiley +2 more sources
SHAP-RC: A Framework for Explaining Annotator Disagreement in Sexism Detection
Abstract The effectiveness of supervised machine learning models is heavily influenced by the quality of training data, which is often shaped by human annotators. Subjective NLP tasks such as hate speech detection, toxicity identification, and sexism classification frequently exhibit annotator disagreement due to differences in individual ...
Madhuri Sawant +3 more
openaire +2 more sources
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Risk Management and Healthcare PolicyJiaxin Zan,1,2 Xiaojing Dong,1,2 Hong Yang,1,2 Jingjing Yan,1,2 Zixuan He,3 Jing Tian,3 Yanbo Zhang1,2,4 1Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, People’s Republic of China; 2Shanxi Provincial Key ...
Zan J +6 more
doaj
Advanced Intelligent Systems, EarlyView.A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley +1 more source
Angewandte Chemie, EarlyView.Dual‐atom catalysts (DACs) for oxygen reduction reaction (ORR), where the dissociative mechanism dominates, show a dual‐Sabatier optima volcano map, diverging from the classical single‐peak volcano of the associative mechanism. Potential‐dependent microkinetic modeling and interpretable machine learning rationalize experimental data and provide design ...
Jin Liu +3 more
wiley +2 more sources
Advanced Intelligent Systems, EarlyView.An instance‐level, model‐agnostic explanation of class differentiation is introduced through SHAP‐LCD, linking probability shifts to feature‐wise Shapley contributions. The method operates on tabular and image data and is released in a fully reproducible implementation, offering a transparent way to examine, at each instance, why predictive models ...
Roxana M. Romero Luna +2 more
wiley +1 more source
American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.ABSTRACT This study aims to prospectively collect harmonized, quantitative, and dimensional psychiatric phenotypes (suicidality, anhedonia, and obsessive‐compulsive symptoms) and information on discrimination, stigma, and unfair treatment in up to 27,500 individuals across diverse ancestries and clinical populations for genetic analysis within the NIMH
Ana M. Diaz‐Zuluaga +36 more
wiley +1 more source