Bitcoin Trend Prediction with Attention-Based Deep Learning Models and Technical Indicators by Ming-Che Lee

“…This study presents a comparative analysis of two advanced attention-based deep learning models—Attention-LSTM and Attention-GRU—for predicting Bitcoin price movements. …”
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Efficient Air Quality Prediction Models Based on Supervised Machine Learning Techniques by Oumoulylte Mariame, El Allaoui Ahmad, Farhaoui Yousef, Boughrous Ali Ait

“…To tackle these issues, it's crucial to set up prediction systems allowing officials to act before high pollution levels occur. …”
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Validation of user-friendly models predicting extracapsular extension in prostate cancer patients by Leandro Blas, Masaki Shiota, Shohei Nagakawa, Shigehiro Tsukahara, Takashi Matsumoto, Ken Lee, Keisuke Monji, Eiji Kashiwagi, Junichi Inokuchi, Masatoshi Eto

“…Objective: There are many models to predict extracapsular extension (ECE) in patients with prostate cancer. …”
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Predicting discharge coefficient of triangular side orifice using ANN and GEP models by Mohamed Kamel Elshaarawy, Abdelrahman Kamal Hamed

“…This study utilized machine learning models to predict the discharge coefficient for a sharp-crested triangular side orifice (TSO). …”
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Improving the Predictability of the Madden‐Julian Oscillation at Subseasonal Scales With Gaussian Process Models by Haoyuan Chen, Emil Constantinescu, Vishwas Rao, Cristiana Stan

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Deep learning models for hepatitis E incidence prediction leveraging Baidu index by Yanhui Guo, Li Zhang, Shengnan Pang, Xiya Cui, Xuechen Zhao, Yi Feng

“…Baidu index proves to be valuable for predicting hepatitis E incidence. Furthermore, stack layers and KAN can also improve the representational ability of LSTM models.…”
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Development of machine learning models for predicting depressive symptoms in knee osteoarthritis patients by Dan Li, Han Lu, Junhui Wu, Hongbo Chen, Meidi Shen, Beibei Tong, Wen Zeng, Weixuan Wang, Shaomei Shang

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Understanding Software Defect Prediction Through eXplainable Neural Additive Models by Ruiqi He, Yong Li, Chi Sun

Subjects: “…Software defect prediction…”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…Results Our model demonstrates a significantly higher correlation coefficient in binding affinity predictions. …”
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A systematic review and meta-analysis of lung cancer risk prediction models by Ghida Khalife, Matilda Nilsson, Lotta Peltola, Juho Waris, Antti Jekunen, Riikka-Leena Leskelä, Heidi Andersén, Mikko Nuutinen, Eija Heikkilä, Susanna Nurmi-Rantala, Paulus Torkki

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The thermal conductivity characteristics and prediction models of limestone sand-yellow soil mixtures by Xiong Liu, Ruiyong Mao, Zujing Zhang, Hongwei Wu, Xing Liang, Jing Chen

“…A backpropagation neural network - based predictive model for thermal conductivity, developed from experimental data, achieved 6.4 % average absolute percentage error, indicating good accuracy.…”
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Prediction of Carbon Dioxide Concentrations in Strawberry Greenhouse by Using Time Series Models by Seung Hyun Shin, Nibas Chandra Deb, Elanchezhian Arulmozhi, Niraj Tamrakar, Oluwasegun Moses Ogundele, Junghoo Kook, Dae Hyun Kim, Hyeon Tae Kim

“…Therefore, the objectives of this study were to predict CO₂ concentrations in the greenhouse by applying time series models using five datasets. …”
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A Comparative Study of Machine Learning Models for Accurate E-Waste Prediction by Mohammed Algafri, Mohammed Sayad, Mohammad A.M. Abdel-Aal, Ahmed M. Attia

“…Future research should explore hybrid models and real-time forecasting to enhance predictive accuracy and sustainability.…”
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Evaluation of mathematical models for predicting medicine distribution into breastmilk - considering biological heterogeneity by Sumin Heo, Sumin Heo, Andrew S. Butler, Marina Stamouli Simoncioni, Sam Moult, Maria Malamatari, Essam Kerwash, Susan Cole

“…Subsequently, alternative methods for predicting lipid and protein binding within the milk, and the effect of ionisation and physicochemical properties were investigated.ResultsExisting models mis-predicted >40% of medications (Phase Distribution model), exhibited extreme sensitivity to milk pH (Log-Transformed model) or exhibited limited sensitivity to changes in creamatocrit (LogPo:w model). …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

“…The performances of the two models are described in detail to show the effectiveness of each of them.…”
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Methods and Evaluation of AI-Based Meteorological Models for Zenith Tropospheric Delay Prediction by Si Xiong, Jiamu Mei, Xinchuang Xu, Ziyu Shen, Liangke Huang

“…Additionally, seasonal variations and station altitude were found to influence the accuracy of ZTD predictions, emphasizing the need for detailed modeling in complex climatic zones.…”
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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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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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