A machine-learned model for predicting weight loss success using weight change features early in treatment by Farzad Shahabi, Samuel L. Battalio, Angela Fidler Pfammatter, Donald Hedeker, Bonnie Spring, Nabil Alshurafa

“…Abstract Stepped-care obesity treatments aim to improve efficiency by early identification of non-responders and adjusting interventions but lack validated models. …”
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Data augmentation using a 1D-CNN model with MFCC/MFMC features for speech emotion recognition by Thomas Mary Little Flower, Thirasama Jaya, Sreedharan Christopher Ezhil Singh

“…Speech emotion recognition (SER) is attractive in several domains, such as automated translation, call centres, intelligent healthcare, and human–computer interaction. Deep learning models for emotion identification need considerable labelled data, which is only sometimes available in the SER industry. …”
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An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures by Xue-Yang Pei, Hai-Bin Huang, Peng Cao

“…An improved Gaussian mixture model (GMM) is proposed in this paper to normalize nonlinear and nonstationary frequency data, enabling effective structural damage detection under variable environmental conditions. …”
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Dominant height growth modeling of Aleppo pine (Pinus halepensis Mill.) in Beni Imloul forest, northern Algeria by Dalila Kherchouche, Mostefa Goubi, Tahar Sghaier, Abdallah Bentouati, Khedidja Zeghichi, Said Slimani

“…This parameter, ranging between 9.13 and 17.77 m with an average of 13.99 m, allowed identifying four quality classes with a 2 m step between each class. The efficiency of the selected model, as productivity estimation-key, was verified by confronting the observed and estimated volumes. …”
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A predictive model of non-suicidal self-injury - a study based on the construction and validation of a nomogram by YuJie Liu, YuJie Liu, TaiMin Wu, Shu Yan, Yang Zhou, Lianzhong Liu

“…Subsequently, a nomogram was developed to enhance the accuracy and efficiency of identifying individuals at high risk for NSSI. …”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…Abstract Parameter identification in a Proton Exchange Membrane Fuel Cell (PEMFC) entails the application of optimization algorithms to ascertain the optimal unknown variables essential for crafting an accurate model that predicts fuel-cell performance. …”
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Machine Learning-Based Prediction of Resilience in Green Agricultural Supply Chains: Influencing Factors Analysis and Model Construction by Daqing Wu, Tianhao Li, Hangqi Cai, Shousong Cai

“…Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. …”
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Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. by Younghee Lee, Xinan Yang, Yong Huang, Hanli Fan, Qingbei Zhang, Youngfei Wu, Jianrong Li, Rifat Hasina, Chao Cheng, Mark W Lingen, Mark B Gerstein, Ralph R Weichselbaum, H Rosie Xing, Yves A Lussier

“…This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.…”
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Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling by Miguel Contreras, Brandon Silva, Benjamin Shickel, Andrea Davidson, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Jeremy Balch, Jiaqing Zhang, Sabyasachi Bandyopadhyay, Tyler Loftus, Kia Khezeli, Gloria Lipori, Jessica Sena, Subhash Nerella, Azra Bihorac, Parisa Rashidi

“…The model integrates vital signs, laboratory results, medications, assessment scores, and patient characteristics, to make predictions, handling sparse, irregular data efficiently. …”
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New Forecasting Metrics Evaluated in Prophet, Random Forest, and Long Short-Term Memory Models for Load Forecasting by Prajowal Manandhar, Hasan Rafiq, Edwin Rodriguez-Ubinas, Themis Palpanas

“…Data mining is vital for smart grids because it enhances overall grid efficiency, enabling the analysis of large volumes of data, the optimization of energy distribution, the identification of patterns, and demand forecasting. …”
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Invasiveness risk assessment of non-native fishes using the AS-ISK model in the rivers of the southern basin of the Caspian Sea by Hossein Rahmani, Seyed Daryoush Moghaddas

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Research progress of near infrared spectroscopy in condiments detection by YU Xinlei, ZHANG Jiahui, LIU Taiang, YIN Mingyu, WANG Xichang

“…This review expounds the classification and common detection methods of condiments, and summarizes the principle, characteristics and rapid detection model of NIRS. The principle, characteristics and rapid detection model of NIRS are outlined. …”
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Research on herd sheep facial recognition based on multi-dimensional feature information fusion technology in complex environment by Fu Zhang, Fu Zhang, Xiaopeng Zhao, Shunqing Wang, Yubo Qiu, Sanling Fu, Yakun Zhang

“…Additionally, the facial expression analysis network attained a test set accuracy of 99.2%, representing a 3.6% increase compared to EfficientNet. The proposed system significantly enhances the accuracy and efficiency of sheep flock monitoring by integrating advanced feature extraction and model optimization techniques. …”
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Dysregulated ac4C modification of mRNA in a mouse model of early-stage Alzheimer’s disease by Hao-Nan Ji, Hai-Qian Zhou, Jing-Bo Qie, Wen-Mei Lu, Hai-Tao Gao, Dan-Hong Wu

“…N4-acetylcytidine (ac4C), the only known form of RNA acetylation in eukaryotes, has recently been shown to regulate mRNA stability and translation efficiency. However, the dysregulation of ac4C associated with abnormal protein expression levels in the brain of early-stage mouse models of AD remains to be elucidated. …”
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Construction and validation of a predictive model for the serum phosphorus reduction after total parathyroidectomy in patients with secondary hyperparathyroidism by Yingnan Feng, Yingnan Feng, Yinghui Zhou, Xiaodong Feng, Qila Sa, Qila Sa, Ningyuan Zhang, Ningyuan Zhang, Wantao Xie, Wantao Xie, Bailiang Liu, Fengyang Chen, Guangming Cheng, Wei Zhang

“…The area under ROC curves (AUC) for the training and validation group were 0.818 (95% CI=0.775~0.861) and 0.840 (95% CI=0.780~0.901, both P<0.05).ConclusionThe established prediction score model for serum phosphorus decrease has a good prediction efficiency which is helpful for the early identification. …”
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Construction of an Artificial Intelligence Model and Application for an Automatic Recognition of Traditional Chinese Medicine Herbals Based on Convolutional Neural Networks by WANG Ganhong, ZHANG Zihao, XI Meijuan, XIA Kaijian, ZHOU Yanting, CHEN Jian

“…After comparing their performance, the EfficientNetB0 model achieved the highest accuracy (99.0%) and AUC (0.994 2) in the validation dataset, and it was selected as the optimal model. …”
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Nonlinear connectedness of conventional crypto-assets and sustainable crypto-assets with climate change: A complex systems modelling approach. by Mushtaq Hussain Khan, Shreya Macherla, Angesh Anupam

“…Earlier studies used classical time series models to forecast the nonlinear connectedness of conventional crypto-assets with CO2 emissions. …”
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AN ANALYSIS OF INVESTMENT DEMAND AND THE DEVELOPMENT TREND OF NON-STATE ENTERPRISES IN VIETNAM by Thi Phuong Dung Ha, Manh Dung Tran

“… This paper studies the investment situation, investment demand, and identification of development trends of non-state enterprises in Hanoi, Vietnam, using the partially adjusted demand model and enterprise identification theory as research approaches. …”
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Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability by Deyan Liu, Yuge Tian, Min Liu, Shangjian Yang

“…Conclusion This study provides a scientific tool for the early screening of MCI in older adults with functional disability and offers an efficient and scalable predictive model for clinical applications and community health services.…”
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Unsupervised Segmentation and Classification of Waveform-Distortion Data Using Non-Active Current by Andrea Mariscotti, Rafael S. Salles, Sarah K. Rönnberg

“…The method can be applied to load identification and classification for non-intrusive load monitoring, with the aim of implementing automatic and unsupervised assessment of load behavior, including transient detection, power-quality issues and improvement in energy efficiency.…”
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