Novel methods for selecting stock portfolio in conditions of uncertainty and forecasting with RR-DEA, ANFIS, FGP: A case study of Tehran stock exchange. by Mohammadmahdi Taheri, Amir Azizi, Emran Mohammadi, Abbas Saghaei

“…These selected stocks are then moved to the second stage, where the ANFIS algorithm is employed in MATLAB to predict the final closing prices and calculate the prediction error (RMSE). …”
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Novel multi-omics analysis revealing metabolic heterogeneity of breast cancer cell and subsequent development of associated prognostic signature by Peng Zhang, Cuicui Li, Fen Li, Jiezhong Wu, Kunpeng Hu, He Huang

“…Drug sensitivity prediction was performed via the OncoPredict tool. Functional assays investigated the oncogenic role of PDCD1 in breast cancer cell lines. …”
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Development, optimization and modelling of performance parameters for remote-controlled mechatronic precision planter using RSM and Hybrid PSO-ANN model by Vimalsinh Vala, Rajvir Yadav, Bikram Jyoti, Ali Salem, Ajay K Roul, Rahul Potdar, Ankur Srivastava, Ahmed Elbeltagi

“…The integration of PSO with prediction models offered insights into enhancing precision planting efficiency and overall crop yield in mechatronic precision planters.…”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…These fields are essential for both mapping ice distribution and predicting icing using physical models combined with numerical weather prediction systems. …”
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Machine learning for medical image classification by Gazi Husain, Jonathan Mayer, Molly Bekbolatova, Prince Vathappallil, Mihir Matalia, Milan Toma

“… This review article focuses on the application of machine learning (ML) algorithms in medical image classification. It highlights the intricate process involved in selecting the most suitable ML algorithm for predicting specific medical conditions, emphasizing the critical role of real-world data in testing and validation. …”
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Integrating Single‐Cell Transcriptomics and Machine Learning to Define an ac4C Gene Signature in Lung Adenocarcinoma by Yuan Wang, Wei Su, Guangyao Zhou, Yijie Wang, Chunnuan Wu, Pengpeng Zhang, Lianmin Zhang

“…Ten machine learning algorithms were applied to develop and validate an ac4C‐related gene signature (ARGSig) for prognosis prediction across multiple independent cohorts. …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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Parameter Estimation for Coupled Hydromechanical Simulation of Dynamic Compaction Based on Pareto Multiobjective Optimization by Wei Wang, Lu-Lu Zhang, Jin-Jian Chen, Jian-Hua Wang

“…Robustness of the back estimated parameters is further illustrated by a forward prediction. Results show that the back-analyzed soil parameters can reasonably predict lateral displacements and give generally acceptable predictions of dynamic compaction for an adjacent location. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…To screen for hub genes associated with OA, a combination of 10 machine learning algorithms and 113 algorithm compositions was integrated. …”
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Halftone images compression of bitplane using run length encoding with confirmation of repeateation by H. K. Al-Bahadily, V. Yu. Tsviatkou, V. K. Kanapelka

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THE ESTIMATION TECHNIQUE OF THE ASSOCIATION INFORMATION EFFICIENCY ABOUT AIR OBJECTS ACCORDING TO SEVERAL SOURCES by A. A. Belous, A. V. Khizhniak, D. S. Sharak, A. S. Bely

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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…Reinforcement Learning (RL) in CRs helps predict spectral changes and identify optimal transmission frequencies. …”
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Artificial intelligence models in corporate financial and accounting processes: systematic literature review by Deivi David Fuentes Doria, Aníbal Toscano Hernández, Johana Elisa Fajardo Pereira

“…The results suggest that supervised models are the most applied in the accounting and financial field, while the algorithms that have been most used are decision trees, support vector machines, random forests, neural networks, and logistic regressions, employed in specific areas of financial fraud, stock market predictions, and cash flow. …”
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Performance of a novel computer‐aided diagnosis system in the characterization of colorectal polyps, and its role in meeting Preservation and Incorporation of Valuable Endoscopic I... by Ejaz Hossain, Mohamed Abdelrahim, Andrea Tanasescu, Masayoshi Yamada, Hiroko Kondo, Shijemi Yamada, Ryuji Hamamoto, Atsushi Marugame, Yutaka Saito, Pradeep Bhandari

“…Recently, a novel AI algorithm for the characterization of polyps was developed by NEC Corporation (Japan). …”
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Modeling of erosion processes in open channels by M. R. Magomedova

“…A technique has been developed for predicting the general erosion of riverbeds and canals, composed of homogeneous and heterogeneous non-cohesive soils. …”
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Synergizing Attribute-Guided Latent Space Exploration (AGLSE) with Classical Molecular Simulations to Design Potent Pep-Magnet Peptide Inhibitors to Abrogate SARS-CoV-2 Host Cell E... by Farhan Ullah, Aobo Xiao, Shahid Ullah, Na Yang, Min Lei, Liang Chen, Sheng Wang

“…Using artificial intelligence (AI), specifically variational autoencoders (VAE) and Wasserstein autoencoders (WAE), we were able to generate a latent space plot that can be surveyed for peptides with known properties and interpolated across a predictive vector between two defined points to identify novel peptides that exhibit dose-responsive antiviral activity. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…Within this framework, deep learning is used to discern the optimal polynomial fitting weights for a physics based polynomial fitting reconstruction on the complex B1+ data. For the prediction of optimal fitting coefficients, three neural networks were separately trained on simulated heterogeneous brain models to predict optimal polynomial weighting parameters in three orthogonal planes. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

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Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling by Qi Qi, Yi Shang

“…We compare their performances in terms of predictive accuracies for the unobserved time points based on their selections of observations. …”
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