GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data by Muhammad Iqbal, Arshad Iqbal, Humaira Ayub, Maqbool Khan, Naveed Ahmad, Yasir Javed, Mohammed Ali Alshara

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Class-Based Constraint-Based Routing with Implemented Fuzzy Logic in MPLS-TE Networks by Michal Pištek, Martin Medvecký

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Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

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Integration of Bulk and Single-Cell Transcriptomics Reveals BCL2L14 as a Novel IGKC+ T Cell-Associated Therapeutic Target in Breast Cancer by He J, Akhtar A, Li J, Wei Q, Yuan Y, Ran J, Ma Y, Chen D

“…To pinpoint key regulatory genes, we applied machine learning algorithms. Based on the hub genes identified, we constructed a prognostic risk model and developed a nomogram to aid clinical decision-making. …”
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Developing a Predictive Model for Stroke Disease Detection Using a Scalable Machine Learning Approach by Assefa Senbato Genale, Tsion Ayalew Dessalegn

“…We have implemented four scalable algorithms: logistic regression, random forest, gradient-boosting tree, and decision tree, using a dataset that was collected from a Medical Quality Improvement Consortium database. …”
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Laparoscopic Suture Gestures Recognition via Machine Learning: A Method for Validation of Kinematic Features Selection by Juan M. Herrera-Lopez, Alvaro Galan-Cuenca, Antonio J. Reina, Isabel Garcia-Morales, Victor F. Munoz

“…In minimally invasive surgery, robotics integration has been crucial, with a current focus on developing collaborative algorithms to reduce surgeons’ workload. Effective human-robot collaboration requires robots to perceive surgeons’ gestures during interventions for appropriate assistance. …”
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Approximating Dynamic Equilibrium Analysis in Multi-Region Network Based on Macroscopic Fundamental Diagram by Bo Liu, Yanqing Cen, Xianghui Song

“…Then, the comparative analysis of the algorithm complexity between the proposed model and the DUE model is given. …”
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Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

“…The proposed ensemble soft voting classifier employs an ensemble of seven machine learning algorithms to provide binary classification, the Naïve Bayes K Nearest Neighbor SVM Kernel Decision Tree Random Forest Logistic Regression and Support Vector Classifier. …”
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Enhancing stroke prediction models: A mixing of data augmentation and transfer learning for small-scale dataset in machine learning by Imam Tahyudin, Ade Nurhopipah, Ades Tikaningsih, Puji Lestari, Yaya Suryana, Edi Winarko, Eko Winarto, Nazwan Haza, Hidetaka Nambo

“…The research compared the prediction accuracy from three solutions: Data Augmentation, Transfer Learning, and the mixing of both methods. …”
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Galaxy Morphological Classification with Zernike Moments and Machine Learning Approaches by Hamed Ghaderi, Nasibe Alipour, Hossein Safari

“…We conclude that these machine learning algorithms are helpful tools for classifying galaxy images. …”
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Machine learning-based predictive modeling of angina pectoris in an elderly community-dwelling population: Results from the PoCOsteo study. by Shahrokh Mousavi, Zahrasadat Jalalian, Sima Afrashteh, Akram Farhadi, Iraj Nabipour, Bagher Larijani

“…We aimed to develop machine learning-based models using multiple algorithms to predict and identify the predictors of angina pectoris in an elderly community-dwelling population.…”
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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

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Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations by Ibrahim Antoun, Ibrahim Antoun, Ahmed Abdelrazik, Mahmoud Eldesouky, Xin Li, Georgia R. Layton, Georgia R. Layton, Georgia R. Layton, Mustafa Zakkar, Mustafa Zakkar, Mustafa Zakkar, Riyaz Somani, Riyaz Somani, G. André Ng, G. André Ng, G. André Ng

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Mapping soil drainage classes: Comparing expert knowledge and machine learning strategies by Danilo César de Mello, Nélida E.Q. Silvero, Bradley A. Miller, Nicolas Augusto Rosin, Jorge Tadeu Fim Rosas, Bruno dos Anjos Bartsch, Gustavo Vieira Veloso, Jean Jesus Macedo Novais, Renan Falcioni, Marcos Rafael Nanni, Marcelo Rodrigo Alves, Elpídio Inácio Fernandes-Filho, Uemeson José dos Santos, José Alexandre Melo Demattê

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Predicting PD-L1 status in NSCLC patients using deep learning radiomics based on CT images by Jiameng Lu, Xinyi Liu, Xiaoqing Ji, Yunxiu Jiang, Anli Zuo, Zihan Guo, Shuran Yang, Haiying Peng, Fei Sun, Degan Lu

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Prediksi Stok dan Pengaturan Tata Letak Barang Menggunakan Kombinasi Algoritma Triple Exponential Smoothing dan FP-Growth by Kristoko Dwi Hartomo, Sri Yulianto Prasetyo, Rahmat Abadi Suharjo

“…Data processing in this research is called data mining using FP-Growth and Triple Exponential Smoothing algorithms. FP-Growth algorithm to find out user behavior patterns can be used to develop Triple Exponential Smoothing decisions and algorithms which are forecasting algorithms for inventory items. …”
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A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–2018 by Wenqiang Wang, Ruiqing Mo, Xingyu Chen, Sijie Yang

“…Subsequently, nine machine learning algorithms—including logistic regression, random forest (RF), radial support vector machine (RSVM), k-nearest neighbors (KNN), XGBoost, LightGBM, decision tree (DT), elastic net regression (ENet), and multilayer perceptron (MLP)—were employed to construct predictive models. …”
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Deep learning-based prediction of individualized Real-time FSH doses in GnRH agonist long protocols by Na Kong, Yu Xia, Zhilong Wang, Hui Zhang, Liyan Duan, Yingchun Zhu, Chenyang Huang, Guijun Yan, Jie Mei, Wujun Li, Haixiang Sun

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Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension by Zunfeng Fu, Jing Wang, Wenyi Shen, Yanqing Wu, Jiajun Zhang, Yan Liu, Chongqiang Wang, Yanlin Shen, Ye Zhu, Weifu Zhang, Chunju Lv, Lin Peng

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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy by Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde

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