MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects by Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, Caterina Bonfiglio, Rossella Donghia, Gianluigi Giannelli, Angela Lombardi, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci

“…This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. …”
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Climate-Based Prediction of Rice Blast Disease Using Count Time Series and Machine Learning Approaches by Meena Arumugam Gopalakrishnan, Gopalakrishnan Chellappan, Santhosh Ganapati Patil, Santosha Rathod, Kamalakannan Ayyanar, Jagadeeswaran Ramasamy, Sathyamoorthy Nagaranai Karuppasamy, Manonmani Swaminathan

“…This work shows how machine learning algorithms can improve the prediction of rice blast, offering vital information for early disease management. …”
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scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data by Lin Yuan, Zhijie Xu, Boyuan Meng, Lan Ye

“…We compare the performance of scAMZI with nine methods (three shallow learning algorithms and six state-of-the-art DL-based methods) on fourteen benchmark scRNA-seq datasets of various sizes (from hundreds to tens of thousands of cells) with known cell types. …”
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Randomized-field microwave-assisted pharmaceutical lyophilization with closed-loop control by Alina A. Alexeenko, Ahmad Darwish, Drew Strongrich, Petr Kazarin, Chanakya Patil, Cole W. Tower, Isaac S. Wheeler, Eric Munson, Qi Zhou, Vivek Narsimhan, Kyu Yoon, Steven L. Nail, Anthony Cofer, Justin Stanbro, Harshil Renawala, Daniel Roth, Francis DeMarco, Justin Griffiths, Dimitrios Peroulis

“…Closed-loop control algorithms enable direct control of the product temperature throughout the drying process, ensuring the material is dried at an optimal rate. …”
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Revolutionizing FANETs With Reinforcement Learning: Optimized Data Forwarding and Real-Time Adaptability by Yasir Ibraheem Mohammed, Rosilah Hassan, Mohammad Kamrul Hasan, Shayla Islam, Huda Saleh Abbas, Muhammad Asghar Khan, Muhammad Attique Khan

“…Nevertheless, traditional routing algorithms, initially developed for terrestrial networks, often fail to meet the unique challenges of FANETs, notably their high mobility and frequently changing network topologies. …”
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Simultaneous and Proportional Myoelectric Control of Multiple Degrees of Freedom in Individuals With Chronic Hemiparesis by Caleb J. Thomson, W. Caden Hamrick, Jakob W. Travis, Michael D. Adkins, Patrick P. Maitre, Steven R. Edgely, Jacob A. George

“…In the adjacent field of myoelectric prostheses, regression algorithms have enabled simultaneous and proportional position control over multiple degrees of freedom (DOFs), which in turn has improved user dexterity. …”
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Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis by Xudong Shen, Xudong Shen, Xudong Shen, Guoxiang Li, Guoxiang Li, Guoxiang Li, Junfeng Yao, Junfeng Yao, Junfeng Yao, Junping Yang, Xiaobo Ding, Xiaobo Ding, Xiaobo Ding, Zongyao Hao, Zongyao Hao, Zongyao Hao, Yan Chen, Yang Chen, Yang Chen, Yang Chen

“…Differentially expressed genes (DEGs) were subsequently analyzed using 10 commonly used machine learning algorithms, generating 101 unique combinations to identify the final DEGs. …”
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Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy by Kausalya Neelavara Makkithaya, Wei-Chung Chen, Chun-Chieh Wu, Ming-Chi Chen, Wei-Hsun Wang, Jackson Rodrigues, Ming-Tsang Wu, Nirmal Mazumder, I-Chen Wu, Guan-Yu Zhuo

“…Unlike previous studies on cancer diagnosis using two-photon microscopy, quantitative analysis or machine learning (ML) algorithms need to be used to determine the subtle structural changes in images and the structural features that are statistically meaningful in cancer development. …”
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Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods by Hsiao-Wei Wang, Yen-Chun Huang, Yu-Wei Fang, Tsrang-Neng Jang, Mingchih Chen, Ming-Hsien Tsai

“…Additionally, five machine learning algorithms assisted in pinpointing critical determinants for AA/AD among those with fluoroquinolones. …”
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Application of Image Computing in Non-Destructive Detection of Chinese Cuisine by Xiaowei Huang, Zexiang Li, Zhihua Li, Jiyong Shi, Ning Zhang, Zhou Qin, Liuzi Du, Tingting Shen, Roujia Zhang

“…This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. …”
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Accuracy of the HeartMate 3 Left Ventricular Assist Device Flow Estimation by Theodor Abart, Marko Grujic, Philipp Aigner, Michael Röhrich, Stefan Jakubek, Daniel Zimpfer, Marcus Granegger

“…This study assessed the HM3 monitoring by describing underlying physical characteristics, estimation algorithms and deriving accuracy of estimates in clinical practice. …”
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Unveiling the power of high-dimensional cytometry data with cyCONDOR by Charlotte Kröger, Sophie Müller, Jacqueline Leidner, Theresa Kröber, Stefanie Warnat-Herresthal, Jannis Bastian Spintge, Timo Zajac, Anna Neubauer, Aleksej Frolov, Caterina Carraro, DELCODE Study Group, Frank Jessen, Simone Puccio, Anna C. Aschenbrenner, Joachim L. Schultze, Tal Pecht, Marc D. Beyer, Lorenzo Bonaguro

“…The comprehensive suite of features of cyCONDOR, including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration of cyCONDOR into clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. …”
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Molecularly redefining small bowel adenocarcinoma to accelerate precision patient care – protocol of a multicenter observational cohort biomarker study by Rasmus Haunstrup Døssing, Julia Johanna Almer Broman, Colm J. O’Rourke, Elizaveta Mitkina Tabaksblat, Jesper Bøje Andersen, Carsten Palnæs Hansen, Tim Svenstrup Poulsen, Estrid V. S. Høgdall, Jakob Hagen Vasehus Schou, Dan Høgdall

“…Secondary outcomes include correlating these subgroups with clinical features, treatment responses, and patient outcomes. Machine learning algorithms will be employed for bioinformatic analyses to interpret molecular data. …”
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Determinants and risk prediction models for frailty among community-living older adults in eastern China by Lin Qi, Lin Qi, Jianyu Liu, Xuhui Song, Xinle Wang, Mengmeng Yang, Xinyi Cao, Yan He

“…Predictive models were constructed using decision trees, random forests, and XGBoost algorithms, implemented in R software (version 4.4.2). …”
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Elucidating the Prognostic and Therapeutic Implications of Insulin Resistance Genes in Breast Cancer: A Machine Learning-Powered Analysis by Lengyun Wei, Dashuai Li, Hongjin Chen, Yajing Pu, Qun Wang, Jintao Li, Meng Zhou, Chenfeng Liu, Pengpeng Long

“…In this study, we employed a suite of machine learning algorithms and statistical methods to construct a robust prognostic model for BC based on insulin resistance-related genes (IRGs). …”
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Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults by Huanghe Zhang, Chuanyan Wu, Yulong Huang, Rui Song, Damiano Zanotto, Sunil K. Agrawal

“…The importance of each type of data is assessed using a brute-force search method, through which the optimal features are selected. AdaBoost algorithms are then utilized to develop predictive models based on the selected features. …”
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Comprehensive Blood Metabolome and Exposome Analysis, Annotation, and Interpretation in E-Waste Workers by Zhiqiang Pang, Charles Viau, Julius N. Fobil, Niladri Basu, Jianguo Xia

“…Two feature detection algorithms, <i>asari</i> and <i>centWave</i>, were applied. …”
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Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Fathi Amsaad, Ansagan Manasov, Salim Hariri, Banu B. Yergaliyeva, Aziz Alotaibi

“…To achieve the clickbait analysis and source rating, the detection of blocklisted/allowlisted source and source rating check algorithms are introduced. The clickbait search process is accomplished by incorporating the binary search features for a faster and more efficient search process for malicious content-detection. …”
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Predicting mechanical properties of low-alloy steels using features extracted from Electron Backscatter Diffraction characterization by Yu Li, Jingxiao Zhao, Xiucheng Li, Zhao Xing, Qiqiang Duan, Xiaojun Liang, Xuemin Wang

“…The GBDT model outperformed other algorithms, demonstrating high accuracy in predicting YS, UTS, and elongation. …”
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Theory of an Automatic Seepage Meter and Ramifications for Applications by Vitaly A. Zlotnik, D. Kip Solomon, David P. Genereux, Troy E. Gilmore, C. Eric Humphrey, Aaron R. Mittelstet, Anatoly V. Zlotnik

“…For example, our analysis determines the timing of the nonmonotonic ASM response to a monotonic linear stream stage variation and explains previously used empirical parabolic approximation for estimating fluxes. We present algorithms for simultaneous inference of vertical interface flux and hydraulic conductivity values together with an example code. …”
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