Explainable artificial intelligence (XAI) for interpreting predictive models and key variables in flood susceptibility by Bahram Choubin, Abolfazl Jaafari, Jalal Henareh, Omid Karimi, Farzaneh Sajedi Hosseini

“…Various machine learning models were tested, with XGBoost achieving the best performance for flood susceptibility prediction (RMSE = 0.333, AUC = 0.890). …”
Get full text

Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

Subjects: Get full text

Assessment of textile sludge pyrolysis behaviour through advance predictive models for bioenergy production by Arslan Khan, Asif Hussain Khoja, Salman Raza Naqvi, Waheed Miran, Imtiaz Ali

“…To optimize the pyrolysis of textile sludge, it is essential to comprehend the complex kinetics involved in its degradation. Machine learning models like Artificial Neural Networks (ANN), Classification and Regression Trees (C&RT), Boosted regression trees (BRT), and K Nearest Neighbors (KNN) employed to predict the activation energy (Ea) with ANN emerging as superior predicting capabilities (R2 = 0.999) over other models. …”
Get full text

Corrosion Risk Assessment in Coastal Environments Using Machine Learning-Based Predictive Models by Marta Terrados-Cristos, Marina Diaz-Piloneta, Francisco Ortega-Fernández, Gemma Marta Martinez-Huerta, José Valeriano Alvarez-Cabal

Subjects: Get full text

Risk factors and predictive models for sequelae of heat stroke primarily involving cerebellar dysfunction by Xiao-Xiao Ni, Gai-Ci Xue, Ye-Qun Guo, Xiao-Juan Xie, Jie Wang, Zhi-Feng Liu

Subjects: Get full text

Evaluating predictive models for hemorrhagic transformation post-mechanical thrombectomy in acute ischemic stroke by Jiaxuan Wang, Jiaxuan Wang, Jianyou You, Hui Yang, Hui Yang, Zhongbin Xia, Xiangbin Wu, Moxin Wu, Moxin Wu, Xiaoping Yin, Xiaoping Yin, Zhiying Chen, Zhiying Chen

“…Therefore, assessing the relevant risks based on predictive models for post-MT HT is necessary. These predictive models incorporate a series of risk factors and conduct statistical analyses to generate corresponding assessment scales, which are then used to evaluate the risk of postoperative bleeding. …”
Get full text

Towards Subject-Specific Strength Training Design through Predictive Use of Musculoskeletal Models by Michael Plüss, Florian Schellenberg, William R. Taylor, Silvio Lorenzetti

“…In a novel approach to release the predictive power of musculoskeletal modelling techniques based on inverse dynamics, flexion/extension and ab-/adduction movements were virtually created. …”
Get full text

Comparative Analysis of ARIMA and lSTM Predictive Models: Evidence from Russian Stocks by A. V. Alzheev, R. A. Kochkarov

Subjects: Get full text

Implementing Symptom-Based Predictive Models for Early Diagnosis of Pediatric Respiratory Viral Infections by Antoni Soriano-Arandes, Cristina Andrés, Aida Perramon-Malavez, Anna Creus-Costa, Anna Gatell, Ramona Martín-Martín, Elisabet Solà-Segura, Maria Teresa Riera-Bosch, Eduard Fernández, Mireia Biosca, Ramon Capdevila, Almudena Sánchez, Isabel Soler, Maria Chiné, Lidia Sanz, Gabriela Quezada, Sandra Pérez, Dolors Canadell, Olga Salvadó, Marisa Ridao, Imma Sau, Ma Àngels Rifà, Esperança Macià, Sílvia Burgaya-Subirana, Mònica Vila, Jorgina Vila, Asunción Mejías, Andrés Antón, Pere Soler-Palacin, Clara Prats

Subjects: Get full text

Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…These algorithms had different advantages and applicable scenarios and could complement each other to improve the precision and robustness of prediction models. To further improve prediction precision, the model parameters were optimized through cross validation to avoid overfitting and improve model performance. …”
Get full text

Assessment of tuberculosis drug efficacy using preclinical animal models and in vitro predictive techniques by Hazem F. M. Abdelaal, Bryan J. Berube, Brendan K. Podell, Matthew H. Harband, Hadley E. Gary, Martin Perez-Jaimes, David F. Ackart, Valerie A. Reese, Sasha E. Larsen, Tiffany Pecor, David Z. Wilkins, Tanya Parish, Sara E. Maloney-Norcross, Jeffrey B. Mecham, Anthony J. Hickey, Susan L. Baldwin, Rhea N. Coler

Get full text

Closing in on Hydrologic Predictive Accuracy: Combining the Strengths of High‐Fidelity and Physics‐Agnostic Models by Vinh Ngoc Tran, Valeriy Y. Ivanov, Donghui Xu, Jongho Kim

“…Abstract Applications of process‐based models (PBM) for predictions are confounded by multiple uncertainties and computational burdens, resulting in appreciable errors. …”
Get full text

Machine Learning in Schizophrenia: A Systematic Review and Meta-Analysis of Diagnostic and Predictive Models by Oluwatobi Idowu, Nicholas Aderinto, Gbolahan Olatunji, Emmanuel Kokori

Get full text

Country-level indices in predictive models of helminth infections: Perspectives from Southeast Asia. by Nathkapach Kaewpitoon Rattanapitoon, Chutharat Thanchonnang, Schawanya Kaewpitoon Rattanapitoon

“…Predictive models integrating country-level indices with individual variables offer valuable insights into soil-transmitted helminth (STH) infection risk among migrant populations. …”
Get full text

Establishing predictive machine learning models for drug responses in patient derived cell culture by Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Gareth Griffiths, Larisa Soldatova, Ross D. King

Get full text

Predictive values of brain age models to rTMS effects in neurocognitive disorder with depression by Hanna LU

Get full text

H∞ filtering of uncertain predictive models: Gain computation using LMI and performance evaluation by Eli G. Pale Ramon, Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Yuriy S. Shmaliy

“…The filter is designed for processes represented in discrete time using the forward Euler method, which allows for predictive modeling. Since the error covariance of a state estimator is a quadratic function of K, a new theorem is proved and a numerical algorithm is developed for computing K using linear matrix inequality (LMI). …”
Get full text

Systematic Analysis and Critical Appraisal of Predictive Models for Lung Infection Risk in ICU Patients by Xuan Wu, Jing Kong, Zihan Sun, Ge Qiu, Zhengxiang Dai

“…Conclusion: Current predictive models for lung infection risk in ICU patients exhibit strong predictive performance. …”
Get full text

Development and validation of web-based, interpretable predictive models for sepsis and mortality in extensive burns by Shi-Qi Wang, Shi-Qi Wang, Kan Qiu, Qi-Rui Zheng, Bing-Jie Zhou, Ming-Yu Li, Hai-Yan Zhong, Yong Chen, Si-Ming Yuan, Si-Ming Yuan

Subjects: Get full text

Dust impact on photovoltaic modules: Global data, predictive models, emphasis on chemical composition by Hussam Almukhtar, Tek Tjing Lie, Wisam Al-Shohani

“…Incorporating 690 global datasets and leveraging Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) in MATLAB, the study integrates key dust chemical components (Si, Fe, Ca, Al) and weight to predict the PV optical properties. This approach enhances models’ predictive accuracy across diverse environmental settings, which in turn enables more accurate forecasting of PV power output and thermal behavior under varying dust conditions, as these optical properties govern the module equations. …”
Get full text