Results 91 to 100 of about 25,341,143 (317)

Leveraging SHAP values for superior prediction and efficient Bayesian optimization in material chemistry

Discover Artificial Intelligence
In recent years, machine learning has played a crucial role in data-driven material development. This study presents a feature extraction method for enhancing the predictive accuracy of regression models.
Takuya Ehiro
doaj   +1 more source

A novel environmental indicator: Compound wind droughts and heat waves for assessing climate-driven ecological and energy sustainability

Ecological Indicators
Compound extremes, specifically concurrent low wind power (wind droughts) and heat waves, threaten ecological stability and renewable energy. However, their dynamics and impacts remain poorly understood.
Jiewen You, Fangxu Yin, Boen Zhang, Mo Zhou, Yamin Qing, Ying Chen, Lu Gao   +6 more
doaj   +1 more source

A Machine Learning Model for Predicting Posthepatectomy Liver Failure After Hepatectomy With Extrahepatic Bile Duct Resection for Perihilar Cholangiocarcinoma: With and Without Indocyanine Green

Annals of Gastroenterological Surgery, EarlyView.
Using machine learning‐based decision tree models, patients with perihilar cholangiocarcinoma undergoing major hepatectomy with extrahepatic bile duct resection were stratified according to the risk of posthepatectomy liver failure. Separate models were developed with and without indocyanine green data, enabling clinically interpretable preoperative ...
Yuki Homma, Hiroki Ohya, Ryusei Matsuyama, Isamu Hosokawa, Tsukasa Takayashiki, Yusuke Ome, Shuichiro Uemura, Ryota Higuchi, Goro Honda, Eiryo Kawakami, Masayuki Ohtsuka, Itaru Endo   +11 more
wiley   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

Machine learning-based prediction of recurrent extrahepatic bile duct stones after common bile duct exploration: a comparative study of models and SHAP-driven interpretability analysis

Frontiers in Medicine
PurposeThis study aimed to construct and compare machine learning models for predicting recurrent extrahepatic bile duct stones after common bile duct exploration and to clarify the contribution of key risk factors using SHAP analysis, thereby providing ...
Yugang Cao, Xun Hu, Jun Guo, Tao Fang
doaj   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study

Intensive Care Medicine Experimental
Background Current machine learning (ML) prediction models offer limited guidance for individualized actionable management. Large language models (LLMs) can transform ML model-predicted risk estimates with Shapley Additive Explanations (SHAP) into ...
Yu-Chang Yeh, Hsin-Yu Yang, Ching-Tang Chiu, Anne Chao, Yu-Chen Chuang, Wing-Sum Chan   +5 more
doaj   +1 more source

Rapid diagnosis of Helicobacter pylori infection status based on endoscopic features and deep learning algorithms

Frontiers in Public Health
Background and aimsEndoscopic visualization for the diagnosis of Helicobacter pylori (HP) infection status is highly important for helping endoscopists quickly understand the status of gastric background mucosa and assisting in subsequent diagnosis and ...
Xinying Yu, Lianyu Li, Qiang He
doaj   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

SHAP model explainability in ECMO–PAL mortality prediction: a critical analysis

Intensive Care Medicine, 2023
Marcos Valiente Fernández, Amanda Lesmes González de Aledo, Francisco de Paula Delgado Moya, Isaías Martín Badía   +3 more
openaire   +3 more sources