Results 171 to 180 of about 44,463 (307)
Understanding Transformer-Based Classifications of Medical Text Using a Large Language Model for the Attribution of Feature Importance: Proof-of-Concept Algorithm Development and Validation Study. [PDF]
Zhou F +6 more
europepmc +1 more source
SHAP Job Burnout Prediction Dataset and Materials"
Synthetic dataset and Python materials for demonstrating SHAP-based machine learning interpretation of job burnout predictors, as described in Weiser (2025).
Eric B Weiser
core +1 more source
ABSTRACT This study examines the determinants of firms' propensity to adopt green buildings in the Euro Stoxx 300 and the S&P 500 indices, during 2012–2023. Using random forest binary classifiers, we assess the relative importance of financial, sectoral, geographic, and climate governance predictors and uncover nonlinear relationships often overlooked ...
María del Carmen Valls Martínez +3 more
wiley +1 more source
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari +2 more
wiley +1 more source
Explainable time-series forecasting with sampling-free SHAP for Transformers. [PDF]
Hertel M +4 more
europepmc +1 more source
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley +1 more source
Evaluating comorbidity scoring systems for flumatinib therapy in chronic myeloid leukemia: a machine learning and SHAP-based predictive analysis. [PDF]
Yang Y, Li Y, Wang J.
europepmc +1 more source
Machine learning‐assisted clone selection for intensified cell culture processes
Abstract Intensified fed‐batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space–time yields relative to traditional, non‐intensified fed‐batch processes. However, the shift towards intensified manufacturing has unexpectedly made optimal clone selection more challenging.
Nicolas Wolnick +6 more
wiley +1 more source
Global Geo-Pharmacogenomics: Environmental Mutational Signatures Drive Population-Level Heterogeneity in Anticancer Drug Response. [PDF]
Jawahar J, James S.
europepmc +1 more source
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao +6 more
wiley +1 more source

