Application of machine learning in predicting fruit waste in a South African fresh produce wholesale market by Ikechukwu Kingsley Opara, Douglas Chinenye Divine, Yardjouma Silue, Umezuruike Linus Opara, Jude A. Okolie, Olaniyi Amos Fawole

“…Using historical data at the case study market from 2021 to 2023, different machine learning algorithms such as Random Forest, Gradient boosting, Decision tree, XGBoost, Extra tree and a Stacked Model were applied. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…This operation preserves the action characteristics of each channel while facilitating a global comparison of these characteristics. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Second, the risk of bias in AI algorithms is still an issue because AI algorithms learn from what is already in print form, thus potentially continuing existing biases in publishing materials (5). …”
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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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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…The results show that random forest and ensemble learning algorithms delivered the highest predictive accuracy, evidenced by the most substantial coefficient of determination (R2) and minimal error metrics. …”
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Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience by Pratap Khattri, Rachel Sayers, Kunwar K. Singh, Ryan Slapikas, Chet Bahadur Tamang, Dinee Tamang, Brad Sagara, Ariel BenYishay

“…We assessed the causal impact of a program promoting sugarcane farming on its adoption and environmental outcomes, measured using multi-temporal satellite imagery, crop phenology, and clustering algorithms, along with machine learning and visual interpretation methods. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…Seven survival machine learning algorithms were used: LASSO, Ridge, RSF, E-NET, GBS, C-GBS, and FS-SVM. …”
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A Multivariate Phenotypical Approach of Sepsis and Septic Shock—A Comprehensive Narrative Literature Review by Alina Tita, Sebastian Isac, Teodora Isac, Cristina Martac, Geani-Danut Teodorescu, Lavinia Jipa, Cristian Cobilinschi, Bogdan Pavel, Maria Daniela Tanasescu, Liliana Elena Mirea, Gabriela Droc

“…Evidence suggests that pulmonary sepsis is one of the most severe forms of sepsis, while liver dysfunction, left ventricular dysfunction, and coagulopathy impact the prognostic. …”
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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

“…Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. …”
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Comparing the potential of tree-based and area-based forest height metrics for aboveground biomass estimation in complex forest landscapes by Weiyan Liu, Yuling Chen, Haitao Yang, Guangcai Xu, Shiyu Yan, Lingjun Li, Ling Chen, Qinghua Guo

“…Two modeling approaches—parametric mixed-effects models (MEM) and non-parametric machine learning (ML) algorithms—were applied to evaluate predictive accuracy. …”
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Machine learning-assisted multi-dimensional transcriptomic analysis of cytoskeleton-related molecules and their relationship with prognosis in hepatocellular carcinoma by Yuxuan Li, Mingbo Cao, Xiaorui Su, Gaoyuan Yang, Yupeng Ren, Zhiwei He, Zheng Shi, Ziyi Hu, Guirong Liang, Qi Zhang, Zhicheng Yao, Meihai Deng

“…Prognostic models were constructed using LASSO regression and random forest algorithms, and validated in two independent cohorts (ICGC LIRI-JP and CHCC-HBV). …”
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OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping by Tianqi Hu, Peng Shen, Yongshuai Zhang, Jiafei Zhang, Xin Li, Chuanzhen Xia, Ping Liu, Hao Lu, Tingting Wu, Zhiguo Han

“…In particular, OpenPheno allows developers to contribute new algorithmic tools, further expanding its capabilities to continuously facilitate the plant phenotyping community. …”
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Design and Operation Principles of a Wave-Controlled Reconfigurable Intelligent Surface by Gal Ben-Itzhak, Miguel Saavedra-Melo, Benjamin Bradshaw, Ender Ayanoglu, Filippo Capolino, A. Lee Swindlehurst

“…Extensive simulation results show that while the envelope detector is simpler to implement, the sample-and-hold circuit has substantially better performance and runs in substantially less time. …”
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Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

“…While in the literature there is much interest in investigating lower limbs gait of patients affected by neurological diseases, such as Parkinson’s Disease (PD), fewer publications involving upper limbs movements are available. …”
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Effect of phosphorus fractions on benthic chlorophyll-a: Insight from the machine learning models by Yuting Wang, Sangar Khan, Zongwei Lin, Xinxin Qi, Kamel M. Eltohamy, Collins Oduro, Chao Gao, Paul J. Milham, Naicheng Wu

“…The SVR analysis demonstrated the dominance of DP and CP upstream and downstream, respectively, while PP was more influential in the middle stream areas. …”
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A Low Power Memory-Integrated Hardware BNN-MLP Model on an FPGA for Current Signals in a Biosensor by Geon-Hoe Kim, Dong-Gyun Kim, Sung-Jae Lee, Jong-Han Kim, Da-Yeong An, Hyejin Kim, Young-Gun Pu, Heejeong Jasmine Lee, Jun-Eun Park, Kang-Yoon Lee

“…This approach enhances accuracy while using binary weights. The BNN-MLP model was designed using TensorFlow for the software model and implemented in hardware at the Register Transfer Level (RTL). …”
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Using Machine Learning to Assess the Effects of Biochar-Based Fertilizers on Crop Production and N₂O Emissions in China by Yuan Zeng, Sujuan Chen, Yunpeng Li, Li Xiong, Cheng Liu, Muhammad Azeem, Xiaoting Jie, Mei Chen, Longjiang Zhang, Jianfei Sun

“…This study uses a global dataset of BBF field experiments to build predictive models with three machine learning algorithms for crop yields and N₂O emissions, and to assess BBFs’ potential to increase yields and mitigate emissions in China’s major crops. …”
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Association of Mediterranean, high-quality, and anti-inflammatory diet with dementia in UK Biobank cohort by Ji-eun Youn, Yu-Jin Kwon, Yae-Ji Lee, Seok-Jae Heo, Ji-Won Lee

“…Dementia incidence was identified using algorithmically defined outcomes based on ICD codes. Fine–Gray subdistribution hazard models adjusted for sociodemographic, genetic, and lifestyle factors were applied to examine the association between dietary indices and dementia risk. …”
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Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net) by Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner, Seong Woo Jeon, Yowhan Son, Andrey Krasovskiy, Woo-Kyun Lee

“…Enhancements included improving backpropagation for optimization and introducing algorithms for national-specific fire ignition dynamics. …”
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