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This section is dedicated to providing you with rigorous and refined academic literature recommendations. 

• Machine learning-based adaptive large neighborhood search algorithm for the integrated vessel scheduling and speed optimization problem in the compound channel

  2025-11-08

  https://doi.org/10.1016/j.asoc.2025.113980

  Read More Read more about Machine learning-based adaptive large neighborhood search algorithm for the integrated vessel scheduling and speed optimization problem in the compound channel

• Temperature prediction and regulation for complex curved parts during automated fiber placement combining FE simulation and machine learning

  2025-11-08

  https://doi.org/10.1016/j.compstruct.2025.119705

  Read More Read more about Temperature prediction and regulation for complex curved parts during automated fiber placement combining FE simulation and machine learning

• Machine learning-driven porosity prediction: A case study from the Cretaceous Mata Series, Canterbury Basin, New Zealand

  2025-11-08

  https://doi.org/10.1016/j.pce.2025.104159

  Read More Read more about Machine learning-driven porosity prediction: A case study from the Cretaceous Mata Series, Canterbury Basin, New Zealand

• Explainable machine learning model for classifying vehicle-impact damage of reinforced concrete bridge columns

  2025-11-08

  https://doi.org/10.1016/j.engstruct.2025.121292

  Read More Read more about Explainable machine learning model for classifying vehicle-impact damage of reinforced concrete bridge columns

• A novel meta-learning-based spatio-temporal modeling approach for thermal error prediction of multiple machine tools with few labeled data

  2025-11-08

  https://doi.org/10.1016/j.engappai.2025.112706

  Read More Read more about A novel meta-learning-based spatio-temporal modeling approach for thermal error prediction of multiple machine tools with few labeled data

• Predicting the Solubility of Lignin via Machine Learning

  2025-11-08

  https://doi.org/10.1021/acs.biomac.5c00874

  Read More Read more about Predicting the Solubility of Lignin via Machine Learning

• Traffic sign detection and recognition in Jordan based on machine learning and deep learning

  2025-11-08

  https://doi.org/10.1016/j.eij.2025.100761

  Read More Read more about Traffic sign detection and recognition in Jordan based on machine learning and deep learning

• SMOTE-Optimized Machine Learning Framework for Predicting Retention in Workforce Development Training

  2025-11-08

  https://doi.org/10.32604/cmc.2025.065211

  Read More Read more about SMOTE-Optimized Machine Learning Framework for Predicting Retention in Workforce Development Training

• Influence of exchange–correlation functional choices on machine learning potential accuracy in the coupled PWDFT-DeePMD framework

  2025-11-08

  https://doi.org/10.1016/j.ssc.2025.116163

  Read More Read more about Influence of exchange–correlation functional choices on machine learning potential accuracy in the coupled PWDFT-DeePMD framework

• Machine learning as a surrogate for FEM: Predicting mechanical properties of tyres

  2025-11-08

  https://doi.org/10.1016/j.aiepr.2025.08.003

  Read More Read more about Machine learning as a surrogate for FEM: Predicting mechanical properties of tyres

• Advancing biogeographical ancestry predictions through machine learning

  2025-11-08

  https://doi.org/10.1016/j.fsigen.2025.103290

  Read More Read more about Advancing biogeographical ancestry predictions through machine learning

• Performance comparison of sampling techniques with machine learning algorithms for churn prediction in telecommunication

  2025-11-08

  https://doi.org/10.1016/j.fraope.2025.100402

  Read More Read more about Performance comparison of sampling techniques with machine learning algorithms for churn prediction in telecommunication

• Sophisticated bio-sensing architecture for anxiety identification using enhanced machine learning techniques

  2025-11-08

  https://doi.org/10.1016/j.medntd.2025.100405

  Read More Read more about Sophisticated bio-sensing architecture for anxiety identification using enhanced machine learning techniques

• Convertible bond return predictability with machine learning

  2025-11-08

  https://doi.org/10.1016/j.finmar.2025.101010

  Read More Read more about Convertible bond return predictability with machine learning

• Machine learning algorithms for predictive maintenance in milling operations

  2025-11-08

  https://doi.org/10.1016/j.nexres.2025.100933

  Read More Read more about Machine learning algorithms for predictive maintenance in milling operations

• Machine Learning Approaches for Predicting Diesel Engine Emissions Using Waste Tire Pyrolysis Oil– Hydrotreated Vegetable Oil Blends

  2025-11-08

  https://doi.org/10.1016/j.psep.2025.108049

  Read More Read more about Machine Learning Approaches for Predicting Diesel Engine Emissions Using Waste Tire Pyrolysis Oil– Hydrotreated Vegetable Oil Blends

• A new method for predicting carbon emissions in energy industry based on CEEMD wavelet denoising and hybrid machine learning

  2025-11-08

  https://doi.org/10.1016/j.egyr.2025.10.002

  Read More Read more about A new method for predicting carbon emissions in energy industry based on CEEMD wavelet denoising and hybrid machine learning

• A few-shot explainable machine learning based framework for designing impact resistance in composite sandwich structures

  2025-11-08

  https://doi.org/10.1016/j.compstruct.2025.119747

  Read More Read more about A few-shot explainable machine learning based framework for designing impact resistance in composite sandwich structures

• Machine learning-based design for high-strength steel tubular section columns

  2025-11-08

  https://doi.org/10.1016/j.istruc.2025.109872

  Read More Read more about Machine learning-based design for high-strength steel tubular section columns

• Predicting bond risk premiums with machine learning: Evidence from China

  2025-11-08

  https://doi.org/10.1016/j.pacfin.2025.102882

  Read More Read more about Predicting bond risk premiums with machine learning: Evidence from China

• Domain knowledge in artificial intelligence: Using conceptual modeling to increase machine learning accuracy and explainability

  2025-11-08

  https://doi.org/10.1016/j.datak.2025.102482

  Read More Read more about Domain knowledge in artificial intelligence: Using conceptual modeling to increase machine learning accuracy and explainability

• Extracting gully using machine learning and deep learning algorithms in the loess hilly and gully region in China

  2025-11-08

  https://doi.org/10.1016/j.iswcr.2025.10.003

  Read More Read more about Extracting gully using machine learning and deep learning algorithms in the loess hilly and gully region in China

• Evaluating machine learning models for predicting the storage performance of polypyrrole-based supercapacitor electrodes

  2025-11-08

  https://doi.org/10.1016/j.est.2025.118943

  Read More Read more about Evaluating machine learning models for predicting the storage performance of polypyrrole-based supercapacitor electrodes

• Construction and application of machine learning models to screen functional ingredients for alcohol metabolism and its mechanism research

  2025-11-08

  https://doi.org/10.1016/j.fbio.2025.107685

  Read More Read more about Construction and application of machine learning models to screen functional ingredients for alcohol metabolism and its mechanism research

• Predicting dislocation patterns and discovering the law of similitude: Machine learning based on fully reversed fatigue of FCC metals

  2025-11-08

  https://doi.org/10.1016/j.ijplas.2025.104535

  Read More Read more about Predicting dislocation patterns and discovering the law of similitude: Machine learning based on fully reversed fatigue of FCC metals

• Predicting the future risk of developing type 2 diabetes in women with a history of gestational diabetes mellitus using machine learning and explainable artificial intelligence

  2025-11-08

  https://doi.org/10.1016/j.pcd.2025.09.006

  Read More Read more about Predicting the future risk of developing type 2 diabetes in women with a history of gestational diabetes mellitus using machine learning and explainable artificial intelligence

• Machine learning in the Australian equity market

  2025-11-08

  https://doi.org/10.1016/j.pacfin.2025.102938

  Read More Read more about Machine learning in the Australian equity market

• Hybrid machine learning model for the prediction of anaemia

  2025-11-07

  https://doi.org/10.1016/j.mlwa.2025.100741

  Read More Read more about Hybrid machine learning model for the prediction of anaemia

• A black-box attack method of machine learning algorithms based on quantum autoencoders

  2025-11-07

  https://doi.org/10.1016/j.physa.2025.131033

  Read More Read more about A black-box attack method of machine learning algorithms based on quantum autoencoders

• Complex network based machine learning method for predicting circuit timing

  2025-11-07

  https://doi.org/10.1016/j.asoc.2025.114100

  Read More Read more about Complex network based machine learning method for predicting circuit timing

• Physics-informed ensemble machine learning for dynamic water quality prediction in water distribution systems

  2025-11-07

  https://doi.org/10.1016/j.jwpe.2025.108841

  Read More Read more about Physics-informed ensemble machine learning for dynamic water quality prediction in water distribution systems

• Private linear equation solving: An application to federated learning and extreme learning machines

  2025-11-07

  https://doi.org/10.1016/j.jocs.2025.102693

  Read More Read more about Private linear equation solving: An application to federated learning and extreme learning machines

• Predicting negative self-rated oral health in adults using machine learning: A longitudinal study in Southern Brazil

  2025-11-07

  https://doi.org/10.1016/j.jdent.2025.106164

  Read More Read more about Predicting negative self-rated oral health in adults using machine learning: A longitudinal study in Southern Brazil

• Prediction and Sensitivity Analysis of Foam Concrete Compressive Strength Based on Machine Learning Techniques with Hyperparameter Optimization

  2025-11-07

  https://doi.org/10.32604/cmes.2025.067282

  Read More Read more about Prediction and Sensitivity Analysis of Foam Concrete Compressive Strength Based on Machine Learning Techniques with Hyperparameter Optimization

• Machine learning and WGCNA reveal the PVT1/miR-143–3p/CDK1 ceRNA axis as a key regulator in NSCLC

  2025-11-07

  https://doi.org/10.1016/j.bbrep.2025.102292

  Read More Read more about Machine learning and WGCNA reveal the PVT1/miR-143–3p/CDK1 ceRNA axis as a key regulator in NSCLC

• Accelerating photovoltaic polymer discovery via machine learning and synthetic accessibility analysis

  2025-11-07

  https://doi.org/10.1016/j.ssc.2025.116182

  Read More Read more about Accelerating photovoltaic polymer discovery via machine learning and synthetic accessibility analysis

• An Analytics Framework for Healthcare Expenditure Forecasting with Machine Learning

  2025-11-07

  https://doi.org/10.1016/j.health.2025.100428

  Read More Read more about An Analytics Framework for Healthcare Expenditure Forecasting with Machine Learning

• Using machine learning classifiers together with discrimination diagrams for validation of rock classification labels

  2025-11-07

  https://doi.org/10.1016/j.acags.2025.100288

  Read More Read more about Using machine learning classifiers together with discrimination diagrams for validation of rock classification labels

• Machine learning-enhanced prediction of size-resolved gas-particle partitioning quotient: Implication for health risk assessment of polycyclic aromatic hydrocarbons

  2025-11-07

  https://doi.org/10.1016/j.jhazmat.2025.140047

  Read More Read more about Machine learning-enhanced prediction of size-resolved gas-particle partitioning quotient: Implication for health risk assessment of polycyclic aromatic hydrocarbons

• Gait and sensory parameters based machine learning classification for detecting cognitive impairment in older adults

  2025-11-07

  https://doi.org/10.1016/j.exger.2025.112915

  Read More Read more about Gait and sensory parameters based machine learning classification for detecting cognitive impairment in older adults

• Estimating the creep rupture time of GFRP bars using machine learning

  2025-11-07

  https://doi.org/10.1016/j.jcomc.2025.100648

  Read More Read more about Estimating the creep rupture time of GFRP bars using machine learning

• Identifying risk factors of post–COVID-19 conditions with machine learning and deep learning algorithms

  2025-11-07

  https://doi.org/10.1016/j.gloepi.2025.100221

  Read More Read more about Identifying risk factors of post–COVID-19 conditions with machine learning and deep learning algorithms

• Multimodal Machine Learning-Based Technical Failure Prediction in Patients Undergoing Transcatheter Aortic Valve Replacement

  2025-11-07

  https://doi.org/10.1016/j.jacadv.2025.102168

  Read More Read more about Multimodal Machine Learning-Based Technical Failure Prediction in Patients Undergoing Transcatheter Aortic Valve Replacement

• Machine learning-assisted identification of core flavor compounds and prediction of core microorganisms in fermentation grains and pit mud during the fermentation process of strong-flavor Baijiu

  2025-11-07

  https://doi.org/10.1016/j.foodchem.2025.146426

  Read More Read more about Machine learning-assisted identification of core flavor compounds and prediction of core microorganisms in fermentation grains and pit mud during the fermentation process of strong-flavor Baijiu

• Machine learning-assisted BMOFs-derived 1D NiCo2O4 nanozyme photoelectrochemical detection of RBP4 for type 2 diabetes diagnosis

  2025-11-07

  https://doi.org/10.1016/j.cej.2025.169192

  Read More Read more about Machine learning-assisted BMOFs-derived 1D NiCo2O4 nanozyme photoelectrochemical detection of RBP4 for type 2 diabetes diagnosis

• An early detection of autism spectrum disorder using machine learning

  2025-11-07

  https://doi.org/10.1016/j.compbiomed.2025.111238

  Read More Read more about An early detection of autism spectrum disorder using machine learning

• A novel grey-box approach to tool wear prediction using machine learning and finite element methods

  2025-11-06

  https://doi.org/10.1016/j.wear.2025.206330

  Read More Read more about A novel grey-box approach to tool wear prediction using machine learning and finite element methods

• High-Fidelity prediction of radioisotope production Cross-Sections using Bayesian neural networks and Auto Machine learning

  2025-11-06

  https://doi.org/10.1016/j.nimb.2025.165887

  Read More Read more about High-Fidelity prediction of radioisotope production Cross-Sections using Bayesian neural networks and Auto Machine learning

• A hybrid physics-informed machine learning framework for water cut prediction in waterflooding reservoirs

  2025-11-06

  https://doi.org/10.1016/j.rineng.2025.107856

  Read More Read more about A hybrid physics-informed machine learning framework for water cut prediction in waterflooding reservoirs

• Data-driven inverse design of graphene Kirigami with negative Poisson's ratio using machine learning and genetic algorithms

  2025-11-06

  https://doi.org/10.1016/j.diamond.2025.112991

  Read More Read more about Data-driven inverse design of graphene Kirigami with negative Poisson's ratio using machine learning and genetic algorithms

• Beyond the surface: Quasi-SMILES machine learning approaches for precise estimation of organic sorption

  2025-11-06

  https://doi.org/10.1016/j.mtcomm.2025.114126

  Read More Read more about Beyond the surface: Quasi-SMILES machine learning approaches for precise estimation of organic sorption

• Methodologies developed for dataset preparation and the interpretability of machine learning algorithms used for the prediction of crack growth rate

  2025-11-06

  https://doi.org/10.1016/j.rineng.2025.107516

  Read More Read more about Methodologies developed for dataset preparation and the interpretability of machine learning algorithms used for the prediction of crack growth rate

• Machine learning approach to identify significant genes and classify cancer types from RNA-seq data

  2025-11-06

  https://doi.org/10.1016/j.gmg.2025.100079

  Read More Read more about Machine learning approach to identify significant genes and classify cancer types from RNA-seq data

• Calibrating machine learning with multi-band photometry: Resolving parameter degeneracies in contact binary NSVS 4803568

  2025-11-06

  https://doi.org/10.1016/j.newast.2025.102484

  Read More Read more about Calibrating machine learning with multi-band photometry: Resolving parameter degeneracies in contact binary NSVS 4803568

• Application of Machine Learning Models for Classifying Wood Surface Defects Using Near-Infrared Spectroscopy

  2025-11-06

  https://doi.org/10.1016/j.microc.2025.115180

  Read More Read more about Application of Machine Learning Models for Classifying Wood Surface Defects Using Near-Infrared Spectroscopy

• Predicting return to sport after multiligament knee injuries using machine learning: development and internal validation of a clinical algorithm

  2025-11-06

  https://doi.org/10.1016/j.knee.2025.10.003

  Read More Read more about Predicting return to sport after multiligament knee injuries using machine learning: development and internal validation of a clinical algorithm

• Machine learning for air quality forecasting: Insights from five provinces of Rwanda

  2025-11-06

  https://doi.org/10.1016/j.sciaf.2025.e02959

  Read More Read more about Machine learning for air quality forecasting: Insights from five provinces of Rwanda

• A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma

  2025-11-06

  https://doi.org/10.1016/j.jhsa.2025.01.021

  Read More Read more about A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma

• A high performance assimilation of surface soil moisture based on a hybrid framework of machine learning and physical hydrological model

  2025-11-06

  https://doi.org/10.1016/j.jhydrol.2025.134513

  Read More Read more about A high performance assimilation of surface soil moisture based on a hybrid framework of machine learning and physical hydrological model

• Authentication of Linderae Radix through plant metabolomics coupled with a machine learning-enhanced in situ hyperspectral imaging approach

  2025-11-06

  https://doi.org/10.1016/j.jpha.2025.101476

  Read More Read more about Authentication of Linderae Radix through plant metabolomics coupled with a machine learning-enhanced in situ hyperspectral imaging approach

• Applications of machine learning algorithms to a sandy beaches ecological database: an empirical and critical comparison

  2025-11-06

  https://doi.org/10.1016/j.ecss.2025.109539

  Read More Read more about Applications of machine learning algorithms to a sandy beaches ecological database: an empirical and critical comparison

• Machine learning-assisted computation of water activity for ionic liquid-based aqueous ternary elements

  2025-11-06

  https://doi.org/10.1016/j.dwt.2025.101484

  Read More Read more about Machine learning-assisted computation of water activity for ionic liquid-based aqueous ternary elements

• Stable dioxin-linked metallophthalocyanine covalent organic frameworks as trifunctional electrocatalysts for overall water splitting and oxygen reduction: A combining density functional theory and machine learning study

  2025-11-06

  https://doi.org/10.1016/j.ijhydene.2025.152132

  Read More Read more about Stable dioxin-linked metallophthalocyanine covalent organic frameworks as trifunctional electrocatalysts for overall water splitting and oxygen reduction: A combining density functional theory and machine learning study

• Beyond Cox models: Assessing the performance of machine-learning methods in non-proportional hazards and non-linear survival analysis

  2025-11-06

  https://doi.org/10.1016/j.compbiomed.2025.111176

  Read More Read more about Beyond Cox models: Assessing the performance of machine-learning methods in non-proportional hazards and non-linear survival analysis

• Physics-informed machine learning meets renewable energy systems: A review of advances, challenges, guidelines, and future outlooks

  2025-11-06

  https://doi.org/10.1016/j.apenergy.2025.126925

  Read More Read more about Physics-informed machine learning meets renewable energy systems: A review of advances, challenges, guidelines, and future outlooks

• Design biomedical β-Ti alloys with exceptional strength-ductility balance via domain knowledge-based machine learning

  2025-11-06

  https://doi.org/10.1016/j.actamat.2025.121550

  Read More Read more about Design biomedical β-Ti alloys with exceptional strength-ductility balance via domain knowledge-based machine learning

• Bonding Time Prediction of AA7075-T6 for Extrusion-Based Additive Manufacturing: Machine Learning and Mathematical Modelling

  2025-11-06

  https://doi.org/10.1016/j.amf.2025.200261

  Read More Read more about Bonding Time Prediction of AA7075-T6 for Extrusion-Based Additive Manufacturing: Machine Learning and Mathematical Modelling

• SmartHeart: A conceptual framework for explainable machine learning in cardiovascular risk prediction

  2025-11-06

  https://doi.org/10.1016/j.compbiomed.2025.111221

  Read More Read more about SmartHeart: A conceptual framework for explainable machine learning in cardiovascular risk prediction

• Leveraging explainable AI framework for predictive modeling of products of microwave pyrolysis of lignocellulosic biomass using machine learning

  2025-11-06

  https://doi.org/10.1016/j.jaap.2025.107249

  Read More Read more about Leveraging explainable AI framework for predictive modeling of products of microwave pyrolysis of lignocellulosic biomass using machine learning

• Machine learning-assisted identification of new psychoactive substances in biological sample using miniaturized ambient mass spectrometer

  2025-11-06

  https://doi.org/10.1016/j.microc.2025.115985

  Read More Read more about Machine learning-assisted identification of new psychoactive substances in biological sample using miniaturized ambient mass spectrometer

• A comparative analysis of machine learning models based on weighted input parameters for V2V path loss prediction in highway, rural, suburban, and urban environments

  2025-11-06

  https://doi.org/10.1016/j.compeleceng.2025.110722

  Read More Read more about A comparative analysis of machine learning models based on weighted input parameters for V2V path loss prediction in highway, rural, suburban, and urban environments

• Identification of key predictors of acute GVHD in pediatric acute Leukemia using machine learning methods

  2025-11-06

  https://doi.org/10.1016/j.trim.2025.102318

  Read More Read more about Identification of key predictors of acute GVHD in pediatric acute Leukemia using machine learning methods

• Machine learning-based algorithm selection for irregular three-dimensional packing in additive manufacturing

  2025-11-06

  https://doi.org/10.1016/j.eswa.2025.127661

  Read More Read more about Machine learning-based algorithm selection for irregular three-dimensional packing in additive manufacturing

• Machine learning and remote sensing for modeling groundwater storage variability in semi-arid regions

  2025-11-06

  https://doi.org/10.1016/j.ige.2025.08.001

  Read More Read more about Machine learning and remote sensing for modeling groundwater storage variability in semi-arid regions

• A Hybrid Framework for Symptom-Based Nerve Weakness Detection Using Machine Learning and Rule-Based Methods

  2025-11-04

  https://doi.org/10.1016/j.fraope.2025.100414

  Read More Read more about A Hybrid Framework for Symptom-Based Nerve Weakness Detection Using Machine Learning and Rule-Based Methods

• Artificial intelligence, machine learning and omic data integration in osteoarthritis

  2025-11-04

  https://doi.org/10.1016/j.joca.2025.10.012

  Read More Read more about Artificial intelligence, machine learning and omic data integration in osteoarthritis

• Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study

  2025-11-04

  https://doi.org/10.1016/j.reia.2025.202712

  Read More Read more about Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study

• Machine learning powered profiling: Rapid identification of Klebsiella Pneumoniae drug resistance from MALDI-TOF MS

  2025-11-04

  https://doi.org/10.1016/j.mimet.2025.107291

  Read More Read more about Machine learning powered profiling: Rapid identification of Klebsiella Pneumoniae drug resistance from MALDI-TOF MS

• Plasma electrolytic oxidation (PEO) coatings on AZ31 magnesium alloy: An interpretable machine-learning study of nano-SiC and process parameters

  2025-11-04

  https://doi.org/10.1016/j.nxmate.2025.101301

  Read More Read more about Plasma electrolytic oxidation (PEO) coatings on AZ31 magnesium alloy: An interpretable machine-learning study of nano-SiC and process parameters

• Using machine learning models to predict vaccine hesitancy: a showcase of COVID-19 vaccine hesitancy in rural populations during the pandemic

  2025-11-04

  https://doi.org/10.1016/j.vaccine.2025.127799

  Read More Read more about Using machine learning models to predict vaccine hesitancy: a showcase of COVID-19 vaccine hesitancy in rural populations during the pandemic

• Regulating humidification-dehumidification systems via machine learning based on quasi-digital twin

  2025-11-04

  https://doi.org/10.1016/j.applthermaleng.2025.128542

  Read More Read more about Regulating humidification-dehumidification systems via machine learning based on quasi-digital twin

• Detonation reaction zone width of CL-20-based aluminized explosive: machine learning prediction, theoretical calculation, and experimental characterization

  2025-11-04

  https://doi.org/10.1016/j.dt.2025.10.019

  Read More Read more about Detonation reaction zone width of CL-20-based aluminized explosive: machine learning prediction, theoretical calculation, and experimental characterization

• Soft sensing of biological oxygen demand in industrial wastewater using machine learning models

  2025-11-04

  https://doi.org/10.1016/j.jwpe.2025.108699

  Read More Read more about Soft sensing of biological oxygen demand in industrial wastewater using machine learning models

• Intelligent detection and analysis of motors based on signal extraction and improved machine learning

  2025-11-04

  https://doi.org/10.1016/j.array.2025.100562

  Read More Read more about Intelligent detection and analysis of motors based on signal extraction and improved machine learning

• Diagnostic and Economic Evaluation of MALDI-TOF MS with Machine Learning for Screening of Johne's Disease from Dairy Cow Serum

  2025-11-04

  https://doi.org/10.3168/jds.2025-27394

  Read More Read more about Diagnostic and Economic Evaluation of MALDI-TOF MS with Machine Learning for Screening of Johne's Disease from Dairy Cow Serum

• Accelerated discovery of functional dyes via machine learning and chemical space exploration

  2025-11-04

  https://doi.org/10.1016/j.ssc.2025.116214

  Read More Read more about Accelerated discovery of functional dyes via machine learning and chemical space exploration

• Estimating market liquidity from daily data: Marrying microstructure models and machine learning

  2025-11-04

  https://doi.org/10.1016/j.finmar.2025.101019

  Read More Read more about Estimating market liquidity from daily data: Marrying microstructure models and machine learning

• Exploring novel Ni-Mn-X based magnetocaloric materials via machine learning with physical descriptors

  2025-11-04

  https://doi.org/10.1016/j.apmt.2025.102923

  Read More Read more about Exploring novel Ni-Mn-X based magnetocaloric materials via machine learning with physical descriptors

• Unveiling Renaissance Drawing Techniques: A Multimodal Machine Learning Approach to the Analysis of Giulio Romano’s Amazzonomachia

  2025-11-04

  https://doi.org/10.1016/j.molstruc.2025.144614

  Read More Read more about Unveiling Renaissance Drawing Techniques: A Multimodal Machine Learning Approach to the Analysis of Giulio Romano’s Amazzonomachia

• Advancing groundwater vulnerability assessment to nitrate contamination: a comprehensive evaluation of index-based, statistical and machine learning approaches with sensitivity analysis

  2025-11-02

  https://doi.org/10.1016/j.jhydrol.2025.134189

  Read More Read more about Advancing groundwater vulnerability assessment to nitrate contamination: a comprehensive evaluation of index-based, statistical and machine learning approaches with sensitivity analysis

• Prediction of geothermal heat flow for sustainable energy applications with sparse geological data using machine learning

  2025-11-02

  https://doi.org/10.1016/j.egyai.2025.100615

  Read More Read more about Prediction of geothermal heat flow for sustainable energy applications with sparse geological data using machine learning

• 2025-10-27 Structure-activity landscapes and synthetic accessibility in machine learning-guided organic semiconductor discovery

  2025-10-27

  https://doi.org/10.1016/j.jphotochem.2025.116877

  Read More Read more about 2025-10-27 Structure-activity landscapes and synthetic accessibility in machine learning-guided organic semiconductor discovery