Artificial intelligence and numerical weather prediction models: A technical survey by Muhammad Waqas, Usa Wannasingha Humphries, Bunthid Chueasa, Angkool Wangwongchai

“…Can artificial intelligence (AI) models beat traditional numerical weather prediction (NWP) models based on physical principles? …”
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Development and Validation of an Incident Hypertension Risk Prediction Model for Young Adults by Jaejin An, Heidi Fischer, Liang Ni, Mengying Xia, Soon Kyu Choi, Kerresa L. Morrissette, Rong Wei, Kristi Reynolds, Paul Muntner, Lisandro D. Colantonio, Andrew E. Moran, Brandon K. Bellows, Monika M. Safford, Norrina B. Allen, Vanessa Xanthakis, Carmen R. Isasi, Linda C. Gallo, Krista M. Perreira, Yiyi Zhang

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A morphometric model to predict the sex of virginia rails (Rallus limicola) by Auriel M.V. Fournier, Mark C. Sheildcastle, Anthony C. Fries, Joseph K. Bump

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A human behavior-based model for respiratory infectious diseases prediction by Zhengwen Ma, Min Zhu, Chen Zhi, Huaguo Zhang, Minye Li, Nan Zhang, Hui Ma, Hui Ma

“…ObjectivesThe research aims to develop a human behavior-based model to predict respiratory infectious diseases.MethodsThis research employs semi-supervised machine learning techniques in conjunction with an RGB-depth camera to collect micro-level data. …”
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Number of Publications on New Clinical Prediction Models: A Bibliometric Review by Banafsheh Arshi, Laure Wynants, Eline Rijnhart, Kelly Reeve, Laura Elizabeth Cowley, Luc J Smits

“… Abstract BackgroundConcerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. …”
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A New Prediction Model of Annular Pressure Buildup for Offshore Wells by Renjun Xie, Laibin Zhang

“…Results indicate that the error of annulus pressure buildup predicted by the multi-string mechanical model proposed in this paper that considers the deformation of the casing sealing section is approximately 13% lower than the one that does not consider this factor. …”
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Comparative Analysis of Advanced Models for Predicting Housing Prices: A Review by Inmaculada Moreno-Foronda, María-Teresa Sánchez-Martínez, Montserrat Pareja-Eastaway

“…ML models (neural networks, decision trees, random forests, among others) provide high predictive capacity and greater explanatory power due to the better fit of their statistical measures. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

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Soft voting ensemble model to improve Parkinson’s disease prediction with SMOTE by Jumanto Unjung, Rofik Rofik, Endang Sugiharti, Alamsyah Alamsyah, Riza Arifudin, Budi Prasetiyo, Much Aziz Muslim

“…This study demonstrates that implementing the soft-voting ensemble-SMOTE method can enhance the model's predictive accuracy.…”
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Prediction Model of Late Fetal Growth Restriction with Machine Learning Algorithms by Seon Ui Lee, Sae Kyung Choi, Yun Sung Jo, Jeong Ha Wie, Jae Eun Shin, Yeon Hee Kim, Kicheol Kil, Hyun Sun Ko

“…Background: This study aimed to develop a clinical model to predict late-onset fetal growth restriction (FGR). …”
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Method for Predicting the Outcome of Burn Injury Based on a Mathematical Model by E. A. Zhirkova, T. G. Spiridonova, O. G. Sinyakova, A. V. Sachkov, A. O. Medvedev, E. I. Eliseenkova, I. G. Borisov, M. L. Rogal, S. S. Petrikov

“…The choice of treatment tactics for a patient with burns should be based on individual prediction of injury outcome. Known models for predicting the outcome of burn injury are inaccurate and do not allow us to determine the probability of different outcomes for a particular patient.AIM OF THE STUDY. …”
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The Usefulness of The Capital Asset Pricing Model in Predicting Total Shareholder Return by Chnar Abdullah Rashid, Rizgar Abdullah Sabir Jaf

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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…With the development of financial technology, the traditional experience-based and single-network credit default prediction model can no longer meet the current needs. …”
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The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…To gauge the predictive efficacy of the models, an array of performance metrics, including R2, RMSE, MSE, WAPE, and the NSE, were employed for assessment. …”
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Research on Annual Runoff Prediction Based on EMD-LSTM-ANFIS Model by HU Shunqiang, CUI Dongwen

“…To improve the accuracy of runoff prediction,this paper proposes a runoff prediction model based on the combination of empirical mode decomposition (EMD),long short-term memory (LSTM) neural network,and adaptive neuro-fuzzy inference system (ANFIS),decomposes the original runoff sequence into multiple regular component sequences through EMD,and reconstructs the phase space of each component sequence by the autocorrelation function method (AFM) and the false nearest neighbor method (FNN) to determine the input and output vectors,establishes the EMD-LSTM-ANFIS prediction model,and constructs the EMD-LSTM,EMD-ANFIS,LSTM,ANFIS as comparison models,as well as predicts and compares the annual runoff of the Longtan Station in Yunnan Province by the five models.The results show that the average relative error of the EMD-LSTM-ANFIS model for the annual runoff prediction is 3.18%,which is reduced by 55.0%、65.2%、68.1%、78.4% compared with the EMD-LSTM,EMD-ANFIS,LSTM,and ANFIS models respectively,with higher prediction accuracy and stronger generalization ability.Therefore,the EMD-LSTM-ANFIS model is feasible and reliable for runoff prediction.…”
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A novel model for predicting immunotherapy response and prognosis in NSCLC patients by Ting Zang, Xiaorong Luo, Yangyu Mo, Jietao Lin, Weiguo Lu, Zhiling Li, Yingchun Zhou, Shulin Chen

“…The RF model demonstrated better predictive performance for immunotherapy responses than the Nomogram model. …”
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VOLATILITY ANALYSIS AND INFLATION PREDICTION IN PANGKALPINANG USING ARCH GARCH MODEL by Desy Yuliana Dalimunthe, Elyas Kustiawan, Khadijah -, Niken Halim, Helen Suhendra

“…This data was obtained through publications from the Central Statistics Agency of Bangka Beliltung Islands Province. The ARCH model is used to handle heteroscedasticity in data, while the GARCH model is a development of the ARCH model and serves as a generalization of the volatility model. …”
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Retracted: Advanced Computing Approach for Modeling and Prediction COVID-19 Pandemic by Applied Bionics and Biomechanics

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Machine Learning Models for Predicting Thermal Properties of Radiative Cooling Aerogels by Chengce Yuan, Yimin Shi, Zhichen Ba, Daxin Liang, Jing Wang, Xiaorui Liu, Yabei Xu, Junreng Liu, Hongbo Xu

“…This study presents a machine-learning-based model for predicting the performance of radiative cooling aerogels (RCAs). …”
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