The place of fast-track technologies in patients with strangulated abdominal hernias without hollow organ resection by B. I. Slonetskyi, I. V. Verbytskyi, V. O. Kotsiubenko

“…The clinical and diagnostic algorithms included laboratory, instrumental and biochemical methods of examination. …”
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Changing the Paradigm for Tractography Segmentation in Neurosurgery: Validation of a Streamline-Based Approach by Silvio Sarubbo, Laura Vavassori, Luca Zigiotto, Francesco Corsini, Luciano Annicchiarico, Umberto Rozzanigo, Paolo Avesani

“…In glioma surgery, maximizing the extent of resection while preserving cognitive functions requires an understanding of the unique architecture of the white matter (WM) pathways of the single patient and of their spatial relationship with the tumor. …”
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High-Performance On-Orbit Intelligent Computing and Real-Time Services for Remote Sensing Satellites Based on Large-Scale Computing Power in Space by Guoping Wang, Gang Wan, Zhijuan Su, Yang Wang, Yutong Jia, Gong Li, Shi Liang

“…This enables the sharing of space computing resources and facilitates satellite-based mission coordination, reducing reliance on ground-based remote sensing satellite services while enhancing the response efficiency of remote sensing application services. …”
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Integrative analysis of semaphorins family genes in colorectal cancer: implications for prognosis and immunotherapy by Jiahao Zhu, Benjie Xu, Zhixing Wu, Zhixing Wu, Zhiwei Yu, Shengjun Ji, Jie Lian, Haibo Lu

“…However, the prognostic value of SEMA-related genes in colorectal cancer (CRC) remains unclear.MethodsWe applied a novel machine learning framework that incorporated 10 machine learning algorithms and their 101 combinations to construct a SEMAs-related score (SRS). …”
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Identification and validation of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral disc degeneration by Hao Li, Lei Miao, Jiayuan Wu, Ye Wang, Jiyuan Xia, Da He

“…SP1 was downregulated in IVDD, while the other three hub genes were upregulated. …”
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Retrieval of Vegetation Indices and Vegetation Fraction in Highly Compact Urban Areas: A 3D Radiative Transfer Approach by Wenya Xue, Liping Feng, Jinxin Yang, Yong Xu, Hung Chak Ho, Renbo Luo, Massimo Menenti, Man Sing Wong

“…The results show that the RMSE is up to 0.050 after correction, while the RMSE is 0.169 before correction. This study makes a contribution to the understanding of the effects of the urban 3D structure and material reflectance on the NDVI and provides insights into the retrieval of the FVC in different urban scenes.…”
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Digital remote monitoring of people with multiple sclerosis by Michelangelo Dini, Michelangelo Dini, Giancarlo Comi, Letizia Leocani, Letizia Leocani, Letizia Leocani

“…We focus on tools and techniques applied to data from wearable sensors, smartphones, and other connected devices, as well as AI-based methods for the analysis of big data.ResultsWearable sensors and machine learning algorithms show significant promise in monitoring motor symptoms, such as fall risk and gait disturbances. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…Globocan predicts that, OSCC will result in 389,846 new cases and 188,438 deaths globally during 2022 while maintaining an extremely poor 5-year survival rate at about 50%. …”
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Bioinformatics screening and clinical validation of CircRNA and related miRNA in male osteoporosis by Jiayi Li, Sijia Guo, Qingyun Sun, Ning An, Jisheng Lin, Qi Fei

“…Then, three genes, including SETD2, ATM and XPO1, were identified as hub genes with four algorithms. Ultimately, the ceRNA network, involving 4 circRNAs, 40 miRNAs, and 592 mRNAs, was obtained. …”
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A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…Additionally, we tested the impact of altering image resolution and data augmentation, while also addressing potential issues related to class detection. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. …”
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From Simulation to Field Validation: A Digital Twin-Driven Sim2real Transfer Approach for Strawberry Fruit Detection and Sizing by Omeed Mirbod, Daeun Choi, John K. Schueller

“…This study demonstrates that integrating digital twins with simulation tools can significantly reduce the need for resource-intensive field data collection while accelerating the development and refinement of agricultural robotics algorithms and hardware.…”
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Machine-Learning-Based Biomechanical Feature Analysis for Orthopedic Patient Classification with Disc Hernia and Spondylolisthesis by Daniel Nasef, Demarcus Nasef, Viola Sawiris, Peter Girgis, Milan Toma

“…(1) <b>Background</b>: The exploration of various machine learning (ML) algorithms for classifying the state of Lumbar Intervertebral Discs (IVD) in orthopedic patients is the focus of this study. …”
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Safe opioid prescribing: a prognostic machine learning approach to predicting 30-day risk after an opioid dispensation in Alberta, Canada by Vishal Sharma, Dean T Eurich, Salim Samanani, Vinaykumar Kulkarni, Luke Kumar

“…C-statistics from the Canadian guidelines ranged from 0.54 to 0.69 while the US guidelines ranged from 0.50 to 0.62. …”
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Comparative analysis of force sensitive resistor circuitry for use in force myography systems for hand gesture recognition by Giancarlo K. Sagastume, Peyton R. Young, Marcus A. Battraw, Justin G. Kwong, Jonathon S. Schofield

“…Further, contemporary machine learning algorithms used to detect hand gestures were unaffected by the circuitry employed. …”
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Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…The E2E ensemble learning method used bagging, AdaBoost, Random Forest, Extra Tree Classifier and XGBoost algorithms as base classifier to perform maximum voting-based prediction. …”
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Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method by Jiawei Zhou, Junhao Wen, Liwen Yao, Zidong Yang, Lijun Xu, Lijian Yao

“…The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Ethically, this review surfaces critical issues, including algorithmic bias, data privacy concerns in mental health analytics, and the interpretability of black-box models used in outbreak surveillance. …”
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Deaths ascribed to non-communicable diseases among rural Kenyan adults are proportionately increasing: evidence from a health and demographic surveillance system, 2003-2010. by Penelope A Phillips-Howard, Kayla F Laserson, Nyaguara Amek, Caryl M Beynon, Sonia Y Angell, Sammy Khagayi, Peter Byass, Mary J Hamel, Anne M van Eijk, Emily Zielinski-Gutierrez, Laurence Slutsker, Kevin M De Cock, John Vulule, Frank O Odhiambo

“…<h4>Methods and findings</h4>Between 2003 and 2010, 15,228 deaths in adults aged 15 years (y) and older were identified retrospectively using the HDSS census and verbal autopsy in rural western Kenya, attributed into broad categories using InterVA-4 computer algorithms; 37% were ascribed to NCDs, 60% to communicable diseases (CDs), 3% to injuries, and <1% maternal causes. …”
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Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain by Shangmin Chen, Yongshan Gao, Lin Du, Mengzhen Min, Lei Xie, Liping Li, Xiaodong Chen, Zhigang Zhong

“…This study included 13,074 middle-aged and older adults from the China health and retirement longitudinal study (wave 2011–2015) to separately develop four-year fall risk prediction models for older adults with and without pain, using five machine learning algorithms with 145 input variables as candidate features. …”
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