AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis by Hind M. AlOsaimi, Aseel M. Alshilash, Layan K. Al-Saif, Jannat M. Bosbait, Roaa S. Albeladi, Dalal R. Almutairi, Alwaleed A. Alhazzaa, Tariq A. Alluqmani, Saud M. Al Qahtani, Sara A. Almohammadi, Razan A. Alamri, Abdullah A. Alkurdi, Waleed K. Aljohani, Raghad H. Alraddadi, Mohammed K. Alshammari

“…AI models, particularly deep learning and machine learning algorithms demonstrated high accuracy in predicting biomarker status. …”
Get full text

A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation by Mumtaz Ali, Ramendra Prasad, Salman Alamery, Aitazaz Ahsan Farooque

“…Consequently, the random forest (RF) algorithm is employed to forecast each of the subseries using PACF-based lagged inputs to construct a fully optimised hybrid RLMD-RF predictive model. …”
Get full text

Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

“…In addition, the SHAP analysis identified the number of stones and the stone CT value as the most critical features influencing the model’s predictions, contributing significantly to its overall predictive performance.ConclusionThe prediction models developed based on three machine learning algorithms can accurately predict the stone-free rate after PCNL in patients with urinary tract stones. …”
Get full text

A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

Subjects: “…thickness prediction…”
Get full text

Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

Subjects: “…Heart-kidney algorithm…”
Get full text

Bridging the Gap Between Machine Learning and Medicine: A Critical Evaluation of the Dworak Regression Grade in Rectal Cancer by Camille Raets, Chaimae El Aisati, Amir L. Rifi, Mark De Ridder, Koen Putman, Johan De Mey, Alexandra Sermeus, Kurt Barbe

Subjects: Get full text

Enhanced clash detection in building information modeling: Leveraging modified extreme gradient boosting for predictive analytics by Ali Shehadeh, Odey Alshboul, Madhar M. Taamneh, Aiman Q. Jaradat, Ahmad H. Alomari

“…The result justifies the model's performance and identifies its potential to streamline predictive analytics in BIM concerning clash detection. …”
Get full text

Predictability of Lifetime Nonsuicidal Self-injury by Symptoms of Sleep Disorders Using a Neural Network Model by Shakiba Rezaei, Azita Chehri, Saeede Sadat Hosseini, Mokhtar Arefi, Hassan Amiri

“…Conclusion: The neural network algorithm can be effectively employed in predicting NSSI by several sleep disorders. …”
Get full text

Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
Get full text

Preoperative prediction of recurrence risk factors in operable cervical cancer based on clinical-radiomics features by Xue Du, Xue Du, Chunbao Chen, Lu Yang, Yu Cui, Min Li

“…ObjectiveTo investigate the value of preoperative prediction of risk factors for recurrence of operable cervical cancer based on the radiomics features of biparametric magnetic resonance imaging (bp-MRI) combined with clinical features.MethodA retrospective collection of cervical cancer cases undergoing radical hysterectomy + pelvic and/or para-aortic lymph node dissection at the Affiliated Hospital of North Sichuan Medical College was conducted. …”
Get full text

Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…The wrapping method was identified as the most effective feature selection algorithm. Based on field conditions, 8 optimal features were selected for prediction. …”
Get full text

A multivariate analysis of the early dropout using classical machine learning and local interpretable model-agnostic explanations by Thanh Hai Nguyen, Phuong Le, Tuyen Thanh Thi Nguyen, Anh Kim Su

“…Consequently, many institutions are focused on identifying key factors that contribute to dropout and implementing strategies to mitigate them. This study aims to predict student dropout rates using classical machine learning algorithms while analyzing the key factors influencing these outcomes in higher education. …”
Get full text

A multivariate analysis of the early dropout using classical machine learning and local interpretable model-agnostic explanations by Thanh Hai Nguyen, Phuong Le, Tuyen Thanh Thi Nguyen, Anh Kim Su

“…Consequently, many institutions are focused on identifying key factors that contribute to dropout and implementing strategies to mitigate them. This study aims to predict student dropout rates using classical machine learning algorithms while analyzing the key factors influencing these outcomes in higher education. …”
Get full text

Software Defect Prediction Using Deep Q-Learning Network-Based Feature Extraction by Qinhe Zhang, Jiachen Zhang, Tie Feng, Jialang Xue, Xinxin Zhu, Ningyang Zhu, Zhiheng Li

“…Unfortunately, all the previous research conducted without effective feature reduction suffers from high-dimensional data, leading to unsatisfactory prediction performance measures. …”
Get full text

Global surface eddy mixing ellipses: spatio-temporal variability and machine learning prediction by Tian Jing, Ru Chen, Chuanyu Liu, Chunhua Qiu, Chunhua Qiu, Cuicui Zhang, Mei Hong

“…These findings highlight the considerable potential of machine learning algorithms in predicting mixing ellipses and parameterizing eddy mixing processes within climate models.…”
Get full text

Digital intelligence and synergy of pollution reduction and carbon reduction: “Dividend” or “gap”? by Jiajia Li, Xianfeng Han, Tonglei Zhang, Jian Xiao, Longtao Chen

“…At the intersection of the “dual carbon” goal and the era of digital intelligence (DI), exploring the synergy between pollution and carbon reduction (SPCR) within the context of DI is important for promoting a comprehensive green transformation of economic and social development. …”
Get full text

Advancing Credit Rating Prediction: The Role of Machine Learning in Corporate Credit Rating Assessment by Nazário Augusto de Oliveira, Leonardo Fernando Cruz Basso

“…This study investigated the potential of machine-learning (ML) algorithms as a more precise and adaptable alternative for credit rating predictions. …”
Get full text

Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

“…Then, four machine learning algorithms and three deep learning networks are evaluated to determine the best predictive model. …”
Get full text

Analysis and Prediction of Wear in Interchangeable Milling Insert Tools Using Artificial Intelligence Techniques by Sonia Val, María Pilar Lambán, Javier Lucia, Jesús Royo

“…This study analyzes the flank wear of cutting tools in milling machines, with an emphasis on evaluating different approaches to predict their lifespan. It compares three distinct modeling approaches for predicting tool lifespan using algorithms: traditional ensemble methods (Random Forest, Gradient Boosting) and a deep learning-based LSTM network. …”
Get full text

Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments by Yang She, Chao Song, Zetian Sun, Bo Li

“…Addressing the path planning problem for multiple wheeled mobile robots (WMRs) in uncertain environments, this paper proposes a multi-WMR path planning algorithm based on the fusion of artificial potential field and model predictive control. …”
Get full text