Risk Model for Predicting Gaps in Surgical Oncology Care Among Patients With Stage I-III Rectal Cancer From KwaZulu-Natal, South Africa by Yoshan Moodley, Willie Brink, Jacqueline van Wyk, Shakeel Kader, Steven D. Wexner, Alfred I. Neugut, Ravi P. Kiran

“…A supervised logistic regression machine learning algorithm was used to train and test an appropriate risk model, which was translated into a nomogram. …”
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Modelling distillate output of a solar distiller with eco-friendly wood-based steam generation basin using machine learning model and starling murmuration optimizer by Mohammed Azmi Al-Betar, Otto L. Muskens, Karrar A. Hammoodi, Mohamed Abd Elaziz, Qusai Yousef Shambour, Salam Fraihat, Ammar H. Elsheikh

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Frequency regulation reserve optimization of wind-PV-storage power station considering online regulation contribution by Changping Sun, Xiaodi Zhang, Wei Zhang, Jiahao Liu, Zubing Zou, Leying Li, Cheng Wang

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Hydrogen Leakage Location Prediction in a Fuel Cell System of Skid-Mounted Hydrogen Refueling Stations by Leiqi Zhang, Qiliang Wu, Min Liu, Hao Chen, Dianji Wang, Xuefang Li, Qingxin Ba

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AI-driven modeling for predicting compressive strength of recycled aggregate concrete under thermal conditions for sustainable construction by Morteza Ghodratnama, Amir R. Masoodi, Amir H. Gandomi

“…This research utilizes sophisticated artificial intelligence (AI) methodologies to forecast the compressive strength of recycled aggregate concrete (RAC) under different temperature scenarios, marking a notable advancement in sustainable construction methodologies. …”
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Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models by Guoli Huang, Sarah Kanaan Hamzah, Pinank Patel, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, S. AbdulAmeer, Mariem Alwan, Zahraa Saad Abdulali, Mahmood Jasem Jawad, Hiba Mushtaq, Mohammad Mahtab Alam, Hojjat Abbasi

“…Among the models tested, the Random Forest algorithm demonstrated outstanding performance, achieving an R2 of 0.955, a Mean Squared Error (MSE) of 0.119, and an Average Absolute Relative Error (AARE%) of 7.683, highlighting its reliability and robustness in predicting ROP. …”
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Cowpea genetic diversity, population structure and genome-wide association studies in Malawi: insights for breeding programs by Michael M. Chipeta, John Kafwambira, Esnart Yohane

“…IntroductionThis study focuses on cowpea, a vital crop for smallholder farmers in sub-Saharan Africa, particularly in Malawi. The research aimed to understand the genetic diversity and population structure of cowpea and to perform genome-wide association studies (GWAS) to identify marker-trait associations (MTAs) for yield and related traits. …”
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Methodological aspects of diagnostics and minimal residual disease monitoring in infant acute leukemias by G. A. Tsaur, A. M. Popov, L. G. Fechina, S. A. Rumyantsev

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Artificial Intelligence in Healthcare: Innovation and Impact in Medical Practice by Amelia-Maria ISAC, Corina VERNIC

“…Studies were selected following PRISMA guidelines, ensuring the inclusion of peer-reviewed research with statistical validation. Data were extracted from two key studies published between 2016 and 2021: (1) “Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs” (Gulshan et al., 2016) and (2) “Deep Learning for Alzheimer’s Disease: A Systematic Review” (Wang et al., 2021). …”
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Using deep learning for thyroid nodule risk stratification from ultrasound images by Yasaman Sharifi, Morteza Danay Ashgzari, Susan Shafiei, Seyed Rasoul Zakavi, Saeid Eslami

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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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Exploring the Role of Peritumoral Edema in Predicting Lung Cancer Subtypes Through T2-FLAIR Digital Subtraction Imaging of Metastatic Brain Tumors by Okan Dilek, Emin Demırel, Zeynel Abidin Tas, Emre Bılgın

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Detection of Water Content of Watermelon Seeds Based on Hyperspectral Reflection Combined with Transmission Imaging by Siyi Ouyang, Siwei Lv, Bin Li

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City-scale industrial tank detection using multi-source spatial data fusion by Zhibao Wang, Mingyuan Zhu, Lu Bai, Jinhua Tao, Mei Wang, Xiaoqing He, Anna Jurek-Loughrey, Liangfu Chen

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Impacts of Spatial and Temporal Resolution on Remotely Sensed Corn and Soybean Emergence Detection by Feng Gao, Martha Anderson, Rasmus Houborg

“…The green-up dates from the remote sensing time series are detected using the within-season emergence (WISE) algorithm and assessed using ground emergence observations and planting records of corn, soybeans, and alfalfa from the Beltsville Agricultural Research Center (BARC) fields in Maryland, USA, from 2019 to 2023. …”
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Grey-Box Modelling of District Heating Networks Using Modified LPV Models by Olamilekan E. Tijani, Sylvain Serra, Patrick Lanusse, Rachid Malti, Hugo Viot, Jean-Michel Reneaume

“…Given the dynamic nature of DHNs and the challenges in predicting disturbances, a dynamic real-time optimisation (DRTO) approach is proposed. However, this research does not implement DRTO; instead, it develops a fast grey-box linear parameter varying (LPV) model for future integration into the DRTO algorithm. …”
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Beyond human-in-the-loop: Sensemaking between artificial intelligence and human intelligence collaboration by Xinyue Hao, Emrah Demir, Daniel Eyers

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METHODS OF MATHEMATICAL STATISTICS AS A MEANS OF PROFESSIONAL COMPETENCE FORMATION OF STUDENTS-ECOLOGISTS by S. I. Toropova

“…The aim of this publication is to reveal the potential of mathematical statistics methods application for the professional competencies formation of future ecologists. Methodology and research methods. Methodological framework of the research is made up of a competency-based approach to the preparation of high school specialists. …”
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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…An extensive dataset of 28,182 PSCs, combinations of six-electron transport layers, ten-hole transport layers, and MAPbI3 absorber layer by varying thickness of each layer, has been generated in the SCAPS-1D simulator. In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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Steatotic liver disease: radiological and ultrasound point of view by Alexey V. Borsukov, Daria Yu. Shestakova

“…The control group included 278 patients without signs of liver steatosis according to instrumental research methods, including 144 (51.8%) men, 40 (48.2%) women aged 18 to 68 years. …”
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