Habitat radiomics predicts occult lymph node metastasis and uncovers immune microenvironment of head and neck cancer by Xinwei Chen, Huan Jiang, Min Pan, Chengmin Feng, Yanshi Li, Lin Chen, Yuxi Luo, Long Liu, Juan Peng, Guohua Hu

“…We used the intratumoral, peritumoral, and habitat volumes of interest (VOIs) to extract radiomics features, respectively. Based on Logistic Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) classifiers, nine radiomics models were built to confirm the optimal predictive performance. …”
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Analysis of Abortion Cases Data at the Referral Hospital of Haho Health District, Notsè – Togo, 2012 – 2017 by Agballa Mébiny-Essoh Tchalla Abalo, Essona Matatom Akara, Hamadi Assane, Degnanou Komi, Edem Kpeglo, Bernard Sawadogo, Simon Antara

“…We aimed to describe data quality, socio-demographic and clinical features of abortions cases. Methods: We conducted a descriptive study based on secondary data analysis of abortion cases admitted at Notsè hospital from January 2012 to December 2017. …”
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Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

“…The study proves a reduction in intervention from 18 to 8 features and a reduction in training time from 1660.5 to 901.66 seconds for comprehensive model development.…”
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ENTREPRENEURIAL COMPETENCE OF THE FUTURE SPECIALIST: PROFESSIONAL AND PERSONAL DIMENSIONS by Kyrylenko Yelisiei

“…The aim of the article is to identify the theoretical foundations of entrepreneurial competence, outline its structure with regard to the specific features of vocational training for students of automotive transport colleges, and emphasise the integration of professional, social, and personal dimensions. …”
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Measuring what matters: Building impact pathways to actionable information for the weADAPT platform by S. Bharwani, K. Williamson, R. Butterfield

“…In addition, users indicated that three features – the weADAPT global case study map (showing location and type of adaptation measure), downloadable newsletter, and thematic content structure – were key in supporting the translation of lessons learned for community-based and policy-based activities, and in discovering and using evidence for diverse research, policy, and practice undertakings. …”
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A nomogram for predicting the nature of thyroid adenomatoid nodules on ultrasound: a dual-center study by Sheng Cheng, Xian-Tao Zeng, Xia Liang, Zhi-Liang Hong, Jian-Chuan Yang, Zi-Ling You, Song-Song Wu

“…Therefore, we aimed to generate and validate a nomogram based on radiomics features and clinical information to predict the nature of TANU.MethodsA total of 200 TANU in 200 patients were enrolled. …”
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Prediction of the 70-gene signature (MammaPrint) high versus low risk by nomograms among axillary lymph node positive (LN+) and negative (LN-) Chinese breast cancer patients, a ret... by Jie Lian, Ru Yao, Ying Xu, Linjuan Tan, Fangyuan Chen, Jiahui Zhang, Yang Qu, Lu Gao, Yanna Zhang, Songjie Shen, Qingli Zhu, Xinyu Ren, Lingyan Kong, Bo Pan, Qiang Sun, Yidong Zhou

“…The models facilitate individualized risk assessment and treatment decision-making, emphasizing tailored approaches based on lymph node status.…”
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Radiomic study on preoperative multi‐modal magnetic resonance images identifies IDH‐mutant TERT promoter‐mutant gliomas by Haoyu Wang, Shuxin Zhang, Xiang Xing, Qiang Yue, Wentao Feng, Siliang Chen, Jun Zhang, Dan Xie, Ni Chen, Yanhui Liu

“…The discovery cohort was split into training and test sets by a 4:1 ratio. A diagnostic model (multilayer perceptron classifier) for detecting the IDHmut pTERTmut gliomas was trained using an automatic machine‐learning algorithm named tree‐based pipeline optimization tool (TPOT). …”
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Preoperative prediction of the Lauren classification in gastric cancer using automated nnU-Net and radiomics: a multicenter study by Bo Cao, Jun Hu, Haige Li, Xuebing Liu, Chang Rong, Shuai Li, Xue He, Xiaomin Zheng, Kaicai Liu, Chuanbin Wang, Wei Guo, Xingwang Wu

“…The CT images were processed by the nnU-Net model to obtain autosegmentation results and extract radiomic features. The least absolute shrinkage and selection operator (LASSO) method selects optimal features for calculating the Radscore and constructing a radiomic model. …”
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Brain functional connectivity characteristics at various levels of inhibitory function in elderly individuals with cognitive impairment by Xin Xin, Zixian Wang, Shuqi Jia, Shufan Li, Qing Liu, Xingze Wang, Xing Wang

“…BrainNet Viewer was utilized to create visualizations of EEG-based brain networks to identify connectivity features. (1) Stroop task accuracy under congruent/incongruent conditions showed a significant positive correlation with MoCA scores (r = 0.599, p < 0.01; r = 0.474, p < 0.01), while reaction times under these conditions exhibited a significant negative correlation with MoCA scores (r=-0.475, p < 0.01; r=-0.354, p < 0.01). (2) Significant differences were observed among the four groups of elderly individuals with cognitive impairment in grip strength, 30-second sit-to-stand, and SPPB performance (P < 0.05). …”
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An integrated, tiered microplastic workflow, supporting rapid broadscale detection options by Samantha K Lynch, Colin L Johnson, Shivanesh Rao, Jaimie Loa-Kum-Cheung, Edwina L Foulsham, Alessandra L Suzzi, Lachlan Hill, Neil Doszpot, Rajitha Athukorala, Uthpala Pinto, Keegan Vickers, Maddison Carbery, Marina F.M. Santana

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Recommendations for uniform terminology in animal-assisted services (AAS) by Amy Johnson Binder, Nancy Parish-Plass, Meg Kirby, Melissa Winkle, Daniela Plesa Skwerer, Laura Ackerman, Cindy Brosig, Wendy Coombe, Esther Delisle, Marie-Jose Enders-Slegers, Jo-Ann Fowler, Laura Hey, Tiffani Howell, Michael Kaufmann, Mariana Kienast, Miyako Kinoshita, Debbie Ngai, Brigitte Wijnen

“…Establishing internationally agreed upon uniform taxonomy, terminology, and definitions is crucial to more accurately reflect the key features of different approaches, to define the scope and competencies for different service providers and their animals, to provide transparency about services for recipients, and to ensure the appropriate preparation, training, and support of the animals that work with them. …”
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Strengthening leadership integrity in religious educational institutions; the phenomenon of muhammadiyah boarding schools in Indonesia by Umar Umar, Punaji Setyosari, Waras Kamdi

“…Continuous learning and integration are key features of cadre training at all stages of adolescence. …”
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A non-invasive computer-aided personalized diagnosis system for Osteopenia and Osteoporosis by Hadeel Osama El-Sisi, Fatma El-Zahraa Ahmed El-Gamal, Noha Ahmed Hikal

“…., normal, Osteopenia, and Osteoporosis) are pre-processed to improve the scans’ quality, and to serve the feature extraction and the construction of the model; (2) the pre-trained VGG16 model is used to identify the descriminative characteristics of each studied group that are then; at stage (3) fed to the SVM classifier to accomplish the diagnosis task, including the severity grading task. …”
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Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography by Alexander Hertel, Mustafa Kuru, Johann S. Rink, Florian Haag, Abhinay Vellala, Theano Papavassiliu, Matthias F. Froelich, Stefan O. Schoenberg, Isabelle Ayx

“…The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. …”
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Solar Energy Datasets of Deep Learning Models Incorporating with GK-2A and ASOS Ground Measurements by Jong-Sung Ha, Seungtaek Jeong, Seyun Min, Yejin Lee, Suhwan Kim, Doehee Han, Jong-Min Yeom

“…The GK-2A satellite features 16 channels, producing radiative channel images at spatial resolutions ranging from 500 m to 2 km, with temporal intervals as short as 2 minutes depending on the area. …”
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MLOmics: Cancer Multi-Omics Database for Machine Learning by Ziwei Yang, Rikuto Kotoge, Xihao Piao, Zheng Chen, Lingwei Zhu, Peng Gao, Yasuko Matsubara, Yasushi Sakurai, Jimeng Sun

“…Empowering these successful machine learning models are the high-quality training datasets with sufficient data volume and adequate preprocessing. …”
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AI assistance enhances histopathologic distinction between sebaceous and squamous cell carcinoma of the eyelid by Jialu Geng, Kai Zhang, Li Dong, Shiqi Hui, Qian Zhang, Zhixi Li, Ruiheng Zhang, Xue Jiang, Mingyang Wang, Shuantao Sun, Hong Zhang, Yunyun Yang, Xinji Yang, Yingshi Piao, Dongmei Li

“…The authors developed a deep learning (DL)-based pathological analysis framework to classify SGC and SC automatically. …”
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Performance analysis of a novel design of an engine piston for a single cylinder by Mnati Hayder M., Hammami Maroua, Haeeb Laith Jaafer, Ksentini Olfa, Feki Nabih, Abbes Mohamed Slim, Haddar Mohamed, Hanon Muammel M.

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A machine learning model for predicting lymph node positivity in ovarian cancer: development, validation, and clinical application by QingYong Guo, Jinji Wang, Ru Chen, LiPing Hu, Wenqiang You

“…This tool can be accessed at http://127.0.0.1:6818 and serves as a practical, evidence-based aid to support individualized treatment decisions and potentially improve patient outcomes. …”
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