Results 211 to 220 of about 776,810 (287)

Machine Learning and Shapley Additive Explanations Value Integration for Predicting the Prognostic of Anti-N-Methyl-D-Aspartate Receptor Encephalitis: Model Development and Evaluation Study. [PDF]

JMIR Med Inform
Wang J, Wu H, Cai H, Wang Y, Gu J.
europepmc   +1 more source

Machine learning‐based prediction of elevated N terminal pro brain natriuretic peptide among US general population

ESC Heart Failure, Volume 12, Issue 2, Page 859-868, April 2025.
Abstract Aims Natriuretic peptide‐based pre‐heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre‐heart failure, has not been well established.
Yuichiro Mori, Shingo Fukuma, Kyohei Yamaji, Atsushi Mizuno, Naoki Kondo, Kosuke Inoue   +5 more
wiley   +1 more source

Nutritional Biomarker-Guided Prediction of Postoperative Pain Outcomes in Elderly Patients Using a Shapley Additive Explanations (SHAP)-Informed XGBoost Approach. [PDF]

Cureus
Ioannidis R, Sarridou D, Bampoulas A, Tsigalou C, Chloropoulou P.   +4 more
europepmc   +1 more source

Machine Learning‐Guided Design of Next‐Generation Battery Materials for Sustainable Energy Storage Systems

Electron, EarlyView.
Machine learning models were developed to predict material stability and sustainability of battery compounds using data‐driven descriptors. The random forest model demonstrated superior performance, enabling efficient screening and identification of environmentally sustainable and thermodynamically stable materials for next‐generation energy storage ...
Godfrey Perfectson Oise, Felix Oshiorenoya Uloko, Immunhierokene Clinton Obrorindo, Augustine Emakpor Otorokpo   +3 more
wiley   +1 more source

A deep learning-clinical combined model with SHapley Additive exPlanations (SHAP) method for assessing the tumor spread through air spaces in lung adenocarcinoma: a multicohort retrospective study. [PDF]

Quant Imaging Med Surg
Zhang R, Sun JS, Liu ZW, Lin YY, Cai XY, Kang LJ, Guo BL, Song YX, Bao CZ, Chen K, Sun Y, Chen YF, Cai ZP, Xie H, Chen HX, Yang SM, Hu QG.   +16 more
europepmc   +1 more source

BIDDING FOR THE SURPLUS: A NON-COOPERATIVE APPROACH TO THE SHAPLEY VALUE. [PDF]

David Wettstein, David Pérez-Castrillo
core  

Long‐term prediction of epilepsy following traumatic brain injury among veterans using routine clinical data

Epilepsia, EarlyView.
Abstract Objective Despite elevated risk for epilepsy following traumatic brain injury (TBI), there are limited tools to assess epilepsy risk following TBI using routine clinical data. The objective of this study was to develop and validate a machine learning approach to predict the onset of posttraumatic epilepsy (PTE) over varying time horizons ...
Mustafa Ozmen, Shashank Vadlamani, James J. Gugger, Megan Amuan, Ramon Diaz‐Arrastia, Mary Jo Pugh, Eamonn Kennedy   +6 more
wiley   +1 more source

Multivariate Quantitative Prediction of Soluble Solids Content, Moisture Content, and Fruit Firmness in 'Dinosaur Egg' Apricot Plum via Near-Infrared Spectroscopy with Cross-Parameter Feature Fusion and SHapley Additive exPlanations-Based Optimization. [PDF]

Foods
Wang Y, Zhu Z, Mao W, Cui K, Yang L, Sun L, Ma W, Ma W, Xiang B.   +8 more
europepmc   +1 more source

DFT and Machine Learning Analysis of Eco‐Friendly Formamidinium Tin Iodide Perovskite Solar Cells: Optimizing Charge Transport Layers Through SCAPS‐1D Simulations

Energy Science &Engineering, EarlyView.
Machine learning using Random Forest, GB, XGBoost, and LightGBM regression algorithms: SHAP plot for PCE. ABSTRACT Tin‐based solar cells are the eco‐friendly alternative to the toxic lead‐based cells that are currently in use. In this context, Formamidinium Tin Iodide (FASnI3) emerges as a promising candidate due to its superior performance, exhibiting
Rabeya Khan, Md Rasidul Islam, I.K. Gusral Ghosh Apurba, Md. Amimul Ihsan, Rahat Ul Nasib, Mohammad Arefin, Md Rifatul Islam, Abu Zahid, Hasnain A. Ziad, Jehan Y. Al‐Humaidi   +9 more
wiley   +1 more source

An Interpretable Predictive Model for Liquid Holdup of Hilly Terrain Oil-Gas Pipelines Based on Machine Learning and Shapley Additive Explanations. [PDF]

ACS Omega
Chen X, Huang S, Guan T, Fu H.
europepmc   +1 more source