Distinguishing Human From Machine: A Review of Advances and Challenges in AI-Generated Text Detection by Serena Fariello, Giuseppe Fenza, Flavia Forte, Mariacristina Gallo, Martina Marotta

“…This advancement offers benefits in various domains, including medicine, education, law, coding, and journalism, but also has negative implications, mainly related to ethical concerns. …”
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Hyperspectral Estimation of Tea Leaf Chlorophyll Content Based on Stacking Models by Jinfeng Guo, Dong Cui, Jinxing Guo, Umut Hasan, Fengqi Lv, Zixing Li

“…In this study, derivative transformations were first applied to preprocess the tea hyperspectral data, followed by the use of the Stable Competitive Adaptive Reweighted Sampling (SCARS) algorithm for feature variable selection. Finally, multiple individual machine learning models and stacking models were constructed to estimate tea LCC based on hyperspectral data, with a particular emphasis on analyzing how the selection of base models and meta-models affects the predictive performance of the stacking models. …”
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Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…Additionally, precipitation displayed a U-shaped relationship with BD risk in both the Subtropical Semi-Humid and Plateau Cold Climate Zones.ConclusionThis study developed a climate zone-specific predictive model for BD, systematically evaluating the interactions between environmental factors and BD dynamics. …”
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Unravelling Antimicrobial Resistance in <i>Mycoplasma hyopneumoniae</i>: Genetic Mechanisms and Future Directions by Raziallah Jafari Jozani, Mauida F. Hasoon Al Khallawi, Darren Trott, Kiro Petrovski, Wai Yee Low, Farhid Hemmatzadeh

“…Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. …”
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Height of Hydraulic Fracture Zone Based on PSO_LSSVM Model by Hebin Zhang, Tingting Wang, Bin Wu, Haijun Feng

“…At the same time, this study develops a particle swarm optimization algorithm based on adaptive inertia weight and a least squares support vector machine model to achieve height prediction of water conducting fracture zones. …”
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Identification of biomarkers for Laryngeal squamous cell carcinoma through Mendelian randomization and integrated bioinformatics analysis by Pengjian Zhang, Weizhang Chen, Kai Chen, Yuanhang Ye, Weijun Wu

“…The differences in immune landscapes between high-risk and low-risk groups were assessed using the CIBERSORT algorithm, and drug sensitivity was analyzed using the “oncoPredict” package. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”
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Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology by Chongchong Yang, Lei Sun, Jun Zhang, Xiaofei Fan, Dongfang Zhang, Tianyi Ren, Minggeng Liu, Zhiming Zhang, Wei Ma

“…Based on the plant spread and plant height, a linear regression prediction of Chinese cabbage weights was conducted, yielding an R² value of 0.76. …”
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Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics by Yuexi Yu, Huiru Liu, Kaipeng Liu, Meiqi Zhao, Yiyan Zhang, Runci Jiang, Fengmei Wang

“…Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. …”
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Future Era of Accountants under the Impact of AI by Guan Ran

“…As AI reshapes the industry, accountants must develop expertise in data analytics, predictive modeling, and cybersecurity to remain competitive. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Strong parameter hierarchy in the interstellar phosphorus chemical network by Marina Fernández-Ruz, Marina Fernández-Ruz, Izaskun Jiménez-Serra, Mario Castro, Mario Castro, Marta Ruiz-Bermejo, Jacobo Aguirre, Jacobo Aguirre

“…In this study, we introduce the Fisher Information Spectral Reduction (FISR) algorithm, a novel and computationally efficient method to reduce the complexity of such sloppy models. …”
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A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review by Ivan Maleš, Marko Kumrić, Andrea Huić Maleš, Ivan Cvitković, Roko Šantić, Zenon Pogorelić, Joško Božić

“…These tools also predict disease severity, aiding decisions between conservative management and surgery. …”
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Prevalence, distribution, and impact of mild cognitive impairment in Latin America, China, and India: a 10/66 population-based study. by Ana Luisa Sosa, Emiliano Albanese, Blossom C M Stephan, Michael Dewey, Daisy Acosta, Cleusa P Ferri, Mariella Guerra, Yueqin Huang, K S Jacob, Ivonne Z Jiménez-Velázquez, Juan J Llibre Rodriguez, Aquiles Salas, Joseph Williams, Isaac Acosta, Maribella González-Viruet, Milagros A Guerra Hernandez, Li Shuran, Martin J Prince, Robert Stewart

“…Country differences changed little (range 0.6%-4.6%) after standardization for age, gender, and education level. In pooled estimates, aMCI was modestly associated with male gender and fewer assets but was not associated with age or education. …”
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A Survey of Matrix Completion Methods for Recommendation Systems by Andy Ramlatchan, Mengyun Yang, Quan Liu, Min Li, Jianxin Wang, Yaohang Li

“…The collaborative filtering problem can be viewed as predicting the favorability of a user with respect to new items of commodities. …”
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The relationship between the CYP2C19*17 genetic polymorphism and the efficacy and safety of diazepam in patients with alcohol withdrawal syndrome by V. Yu. Skryabin, M. S. Zastrozhin, E. A. Grishina, K. A. Ryzhikova, V. V. Shipitsyn, I. V. Barna, T. E. Galaktionova, A. S. Sorokin, E. A. Bryun, D. A. Sychev

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Graph Knowledge Structure for Attentional Knowledge Tracing With Self-Supervised Learning by Zhaohui Liu, Sainan Liu, Weifeng Gu

“…In addition, we incorporate the improved representation algorithm into the loss function to handle data sparsity, thereby improving prediction accuracy. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…Methodologically, the study used CNN algorithms optimised by Bayesian techniques for the prediction of eight water quality indices, coupled with SHAPley Additive exPlanations (SHAP) analysis under XAI to interpret the complex decision-making processes of these models. …”
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Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…Our results yield low accuracy and ROC results of within $$0.49-0.52$$ 0.49 - 0.52 and $$0.49-0.52$$ 0.49 - 0.52 respectively, indicating failure in predicting random data demonstrates efficient randomness prediction resiliency of the MR-PUF. …”
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AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view by Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekani, Ahmad Bitarafan-Rajabi, Kouhyar Geravand, Parham Geramifar

“…The MLP-predicted dose values across all organs represented superior performance with the lowest mean absolute error in the liver but higher in the spleen and salivary glands. …”
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