Results 131 to 140 of about 44,463 (307)

SHAP dependence plot PTB1–3,000 sampling.

Legend: The positive association between PTB (preterm birth) and TMD (temporomandibular disease) was more apparent in Figs 1–4. Here, points with low TMD values and low SHAP values for PTB were positioned in the left bottom, while points with high TMD ...
In-Seok Song (17720212), Eun Sun Kim (843999), Sohee Jung (6553586), Kwang-Sig Lee (7587932), Jisu Kim (841223), Sunwoo Nam (8475585), Ki Hoon Ahn (10221265)   +6 more
core   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Interpretable machine learning model for comparing and validating three diagnostic criteria for bronchopulmonary dysplasia in predicting value of respiratory prognosis of preterm infants: a retrospective cohort study

Frontiers in Pediatrics
BackgroundComparison and validation of the predictive value of three diagnostic criteria for bronchopulmonary dysplasia for respiratory prognosis of preterm infants with gestational age <32 weeks.MethodsThis retrospective cohort study was conducted to
Qiqi Bu, Xin Wang, Yanyan Wu, Yingyuan Wang, Rui Li, Yanmei Zhao, Caijun Wang, Guiying Sun, Wenqing Kang   +8 more
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Interpretable Ensemble-Based Intrusion Detection Using Feature Selection on the ToN_IoT Dataset

JISA (Jurnal Informatika dan Sains)
With With the rapid growth of IoT, securing interconnected devices against cyber threats has become critical. IoT datasets such as ToN-IoT are often high-dimensional, which poses challenges for efficient and accurate intrusion detection.
Vaman Shakir Sulaiman, Firas Mahmood Mustafa   +1 more
doaj   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Interpretable artificial intelligence for predicting blood transfusion after surgery for femoral shaft fractures: A retrospective analysis

Indian Journal of Anaesthesia
Background and Aims: Blood transfusions are often necessary in the surgical repair of orthopaedic fractures. However, these transfusions are associated with significant morbidity.
Rameshbabu Manyam, Puneet Gupta, Pengfei Lou, Rui Guo, Andrew Carro, Eric R. Heinz   +5 more
doaj   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Feature representation for explainable CRISPR off-target prediction and base editing efficiency

Frontiers in Bioinformatics
IntroductionThe interaction between guide RNAs (gRNAs) and target DNA sequences is a critical factor in the effectiveness of CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9) gene editing.
Faiza Hasin, Faiza Hasin, Michele Minervini, Corrado Mencar, Corrado Mencar, Giuseppe Ventrella, Arianna Consiglio, Alessandro Orro, Tommaso Selmi   +8 more
doaj   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source