Explainable machine learning-driven models for predicting Parkinson’s disease and its prognosis: obesity patterns associations and models development using NHANES 1999–2018 data by Jiaxin Fan, Shuai Cao, Hang Peng, Yuanjie Zhi, Shuqin Zhan, Rui Li

Subjects: Get full text

Non-Destructive Detection of Current Internal Disorders and Prediction of Future Appearance in Mango Fruit Using Portable Vis-NIR Spectroscopy by Jasciane da Silva Alves, Bruna Parente de Carvalho Pires, Luana Ferreira dos Santos, Tiffany da Silva Ribeiro, Kerry Brian Walsh, Ederson Akio Kido, Sergio Tonetto de Freitas

“…A recommendation is made for the consideration of ensemble models in future. The ability to predict the development of the disorder using spectra of at-harvest fruit offers the potential to guide postharvest practices and reduce incidence of internal disorders in mangoes.…”
Get full text

Prediction of absolute bioavailability of medicines in children: based on predicted pediatric clearance from adults by Iftekhar Mahmood

“…Systemic and oral clearances of these medicines in children were predicted using age-dependent exponent (ADE) allometric model using observed adult clearance values. …”
Get full text

Predictive Factors for Fetal Growth Restriction in Patients with Preeclampsia: A Clinical Prediction Study by Yan M, Li F, Jun S, Li L, You W, Hu L

Subjects: “…preeclampsia fetal growth restriction predictive model nomogram risk factors…”
Get full text

Specifics of predicting the profitability of individual bank products based on machine learning by Inna Strelchenko, Dmytro Stognii, Anatolii Strelchenko

“…It explores the use of machine learning to build adaptive predictive models that can identify hidden patterns in financial data and provide more accurate estimates of the future profitability of banking products. …”
Get full text

Nomogram for predicting mortality in hospitalized patients with infective endocarditis by Yuqiong An, Xiaojuan Wang, Zhen Wang, Kundi Chen, Fang Nie

Subjects: Get full text

PREDICTING THE VOLUME OF INVESTMENTS INTO CAPITAL ASSETS IN THE INDUSTRY OF KYRGYZ REPUBLIC by T. V. Palagina

Subjects: Get full text

Using Hybrid Neural Networks to Improve Traffic Prediction and Congestion Management by Ali Abd Samir

Subjects: “…Traffic Prediction, Deep Learning, Graph-Based Models, DCRNN, METR-LA, Congestion Management…”
Get full text

Multi-Sensor Heterogeneous Signal Fusion Transformer for Tool Wear Prediction by Ju Zhou, Xinyu Liu, Qianghua Liao, Tao Wang, Lin Wang, Pin Yang

Subjects: “…tool wear prediction…”
Get full text

Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins by Senlin Tang, Fubao Sun, Wenbin Liu, Hong Wang, Yao Feng, Ziwei Li

“…Abstract Streamflow prediction in ungauged basins (PUB) is challenging, and Long Short‐Term Memory (LSTM) is widely used to for such predictions, owing to its excellent migration performance. …”
Get full text

Predict the carcinogenicity of compounds with SGCN by Wei Ruobing, He Jiafeng, Qiu Xiaofang, Liu Qi

“…The results showed that when compared to other models, the classification model of the SGCN was more suited to predicting the carcinogenicity of compounds and had an overall classification accuracy of 96.9%, which showed that the SGCN model could accurately classify chemicals and had considerable potential in practical applications.…”
Get full text

A fair and efficient two-step procedure for sugarcane properties prediction based on near-infrared spectra by Luiz Alexandre Peternelli, Andréa Carla Bastos Andrade, Cristina Silva Dias, Reinaldo Francisco Teófilo

Get full text

An artificial intelligence model to predict mortality among hemodialysis patients: A retrospective validated cohort study by Zhong Peng, Shuzhu Zhong, Xinyun Li, Fengyi Yu, Zixu Tang, Chunyuan Ma, Zihao Liao, Song Zhao, Yuan Xia, Haojun Fu, Wei Long, Mingxing Lei, Zhangxiu He

Subjects: Get full text

The challenges for developing prognostic prediction models for acute kidney injury in hospitalized children: A systematic review by Chen Wang, Xiaohang Liu, Chao Zhang, Ruohua Yan, Yuchuan Li, Xiaoxia Peng

Subjects: Get full text

Comparison of exposure assessment models, expert judgment and Bayes analysis, in Prediction of the tile industry respiratory exposures by MJ Zare Sakhvidi, H Mihanpoor, H Falahzadeh, M Mostaghaci, GH Halvani, F Samouri

Get full text

Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…Conclusion This simplified prediction model effectively identifies the risk of LAT in patients with paroxysmal AF, providing a valuable tool for clinical decision-making. …”
Get full text

Preliminary investigation on predicting postoperative glioma recurrences based on a multiparametric radiomics model by Fang-Xiong Fu, Fang-Xiong Fu, Guo Li, Lan Hong, Wang-Sheng Chen

“…This study aimed to evaluate the performance of a magnetic resonance imaging (MRI)-based multiparametric radiomics model for the early prediction of postoperative recurrences.MethodsThe data from 60 patients who met the inclusion criteria between 2000 and 2021 were collected in this study. …”
Get full text

A novel deep learning model for predicting marine pollution for sustainable ocean management by Michael Onyema Edeh, Surjeet Dalal, Musaed Alhussein, Khursheed Aurangzeb, Bijeta Seth, Kuldeep Kumar

Get full text

Fungi-Kcr: a language model for predicting lysine crotonylation in pathogenic fungal proteins by Yong-Zi Chen, Yong-Zi Chen, Xiaofeng Wang, Zhuo-Zhi Wang, Haixin Li, Haixin Li

“…Moreover, our results indicate that a general predictive model performs better than species-specific models. …”
Get full text

A Model for Predicting IoT User Behavior Based on Bayesian Learning and Neural Networks by Xin Xu, Chengning Huang, Yuquan Zhu

“…To facilitate the allocation of energy and resources in the Internet of Things system, this paper presents a model for predicting user behavior in Internet of Things environments. …”
Get full text