An Integrated Supply Chain Model for Predicting Demand and Supply and Optimizing Blood Distribution by Pooria Bagher Niakan, Mehdi Keramatpour, Behrouz Afshar-Nadjafi, Alireza Rashidi Komijan

“…<i>Method</i>: Classic time-series models are applied to predict future supply chain circumstances, addressing uncertainty in blood demand and the need for timely supply. …”
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Predicting the hospitalization burdens of patients with mental disease: a multiple model comparison by Lu Hou, Lu Hou, Jing Zhang, Jing Zhang, Li Li, Yelin Weng, Ziyu Yang, Zhiguo Liu

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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

Subjects: “…grey model…”
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Stroke Lesion Prediction by Bille-Viper-Segmentation with Tandem-MU-net Model by Beevi Fathima, N Santhi Dr, N Ramasamy Dr

“…Stroke is a critical condition marked by the death of brain cells due to inadequate blood flow, necessitating improved predictive models for stroke lesions. The accuracy and flexibility required to forecast and classify stroke lesions is lacking in current approaches, which compromise patient outcomes. …”
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Improving prediction accuracy in agricultural markets through the CIMA-AttGRU model. by Yankun Jiang, Jinhui Liu, Xiaotuan Li

“…This model uniquely integrates Collective Intrinsic Mode Analysis (CIMA) with an Attention-Gated Recurrent Unit (AttGRU), leveraging the strengths of both techniques to enhance predictive accuracy and adaptability. …”
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A quantitatively interpretable model for Alzheimer’s disease prediction using deep counterfactuals by Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung, Eunsong Kang, Kun Ho Lee, Heung-Il Suk

“…Deep learning (DL) for predicting Alzheimer’s disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. …”
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Local Functional Coefficient Autoregressive Model for Multistep Prediction of Chaotic Time Series by Liyun Su, Chenlong Li

“…Thirdly, we use the nearest neighbor points to get a LFAR model. The proposed model’s parameters are selected by modified generalized cross validation (GCV) criterion. …”
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Predicting the prognosis of epithelial ovarian cancer patients based on deep learning models by Zihan Li, Jiao Wang, Yixin Zhang, Zhen Yang, Fanchen Zhou, Xueting Bai, Qian Zhang, Wenchong Zhen, Rongxuan Xu, Wei Wu, Zhihan Yao, Xiaofeng Li, Yiming Yang

“…Survival outcomes were compared between different risk subgroups based on Kaplan-Meier analysis. Three predictive models were developed using machine learning(ML) techniques, and another was a nomogram based on COX proportional risk regression for estimating 3-year and 5-year overall survival in patients with epithelial ovarian cancer. …”
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Development and validation of prediction models for diabetic retinopathy in type 2 diabetes patients by Shadi Naderyan Feˈli, Mohammad Hassan Emamian, Mehdi Yaseri, Hamid Riazi-Esfahani, Hassan Hashemi, Akbar Fotouhi, Kamran Yazdani

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Prediction Model of Material Properties Based on Feature Fusion and Convolutional Neural Network by SHI Jingchen, LIU Feining, WANG Wenjie, ZHAO Rui

“…Aiming at the problem that most machine learning models need a lot of prior knowledge and manual selection of feature vectors in the prediction of material properties, a convolutional neural network model OPCNN (Orbital of Electron and Periodic table CNN) is established by feature fusion based on two descriptors, electronic orbit matrix and periodic table method. …”
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Stock Predictions Based on Time Series Models - The Case of Pepsi Research Background by Liu Leyi, Wang Wenhao, Zhao Yijing

“…A statistical model widely used in time series analysis and prediction is Auto Regressive Integrated Moving Average (ARIMA) model. …”
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Time series models for prediction of leptospirosis in different climate zones in Sri Lanka. by Janith Warnasekara, Suneth Agampodi, Rupika Abeynayake

“…These predictive models could be effectively used in public health planning purposes.…”
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A prognostic prediction model for advanced gastric cancer based on Ki67 by NIU Linjun*，LI Xinzhong，LYU Yongjian

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Fractal-Based Thermal Conductivity Prediction Modeling for Closed Mesoporous Polymer Gels by Haiyan Yu, Mingdong Li, Ning Guo, Anqi Chen, Haochun Zhang, Mu Du

“…The conductive thermal conductivity component was formulated based on a diagonal cross fractal structure, while the radiative component was derived considering microscale radiative effects. Model predictions exhibit strong agreement with experimental results from various mesoporous polymer gels, achieving a prediction error of less than 11.2%. …”
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Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model by F.C. Ihenetu, C.I. Okoro, M.M. Ozoude, K.E. Dunga, C. Nwaoha

“…This study aimed to develop and validate a Clinical Prediction Rule (CPR) for predicting the presence of S. pyogenes in throat swabs from children under 12. …”
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Comparative Analysis of Diabetes Prediction Models Using the Pima Indian Diabetes Database by Zhao Yize

“…This study provides an in-depth review and comparison of diabetes prediction models using the Pima Indian Diabetes database. …”
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Comparative Analysis of Machine Learning Models for CO Emission Prediction in Engine Performance by Beytullah Eren, İdris Cesur

“…This study presents a comparative analysis of machine learning models for predicting carbon monoxide (CO) emissions in automotive engines. …”
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Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease by Fang Wang, He Zhou, Yujie Zhang, Yu Da, Tiantian Zhang, Yanting Shi, Tong Wu, Jie Liang

“…Aims: This study aimed to develop a model for predicting clinical remission probability for Crohn’s disease patients with Adalimumab at 12 weeks. …”
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Improving parking availability prediction in smart cities with IoT and ensemble-based model by Stéphane Cédric Koumetio Tekouabou, El Arbi Abdellaoui Alaoui, Walid Cherif, Hassan Silkan

“…We propose in this paper a new system that integrates the IoT and a predictive model based on ensemble methods to optimize the prediction of the availability of parking spaces in smart parking. …”
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Student Major Subject Prediction Model for Real-Application Using Neural Network by Aminul Islam, Jesmeen Mohd Zebaral Hoque, Md. Jakir Hossen, Halizah Basiron, Chy. Mohammed Tawsif Khan

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