Notice of Violation of IEEE Publication Principles: Ground-Based Cloud Image Recognition System Based on Multi-CNN and Feature Screening and Fusion by Ma Jingyi, Tiejun Zhang, Jing Guodong, Yan Wenjun, Yang Bin

“…In addition, ablation experiments show that the multi-scale feature extraction, screening and local feature coding in this paper have a significant effect on improving the algorithm’s ability to distinguish different cloud images.…”
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Aggregation of cardiovascular risk factors in a cohort of 40-year-olds participating in a population-based health screening program in Sweden by Beata Borgström Bolmsjö, Emelie Stenman, Anton Grundberg, Kristina Sundquist

“…SCORE2 was calculated according to the algorithm provided by the SCORE2 working group and ESC (European Society of Cardiology) Cardiovascular Risk Collaboration. …”
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An Integrated Fault Diagnosis Method for Rotating Machinery Based on Improved Multivariate Multiscale Amplitude-Aware Permutation Entropy and Uniform Phase Empirical Mode Decomposi... by Jiancheng Gong, Xiaoqiang Yang, Fan Pan, Wuqiang Liu, Fuming Zhou

“…This algorithm is combined with the Uniform Phase Empirical Mode Decomposition (UPEMD) method and the t-distributed Stochastic Neighbor Embedding (t-SNE) method, forming a new time-frequency multiscale feature extraction method. …”
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A Bioinert Hydrogel Framework for Precision 3D Cell Cultures: Advancing Automated High‐Content and High‐Throughput Drug Screening by Hyunsu Jeon, Tiago Thomaz Migliati Zanon, James Carpenter, Aliciana Ilias, Yamil Colón, Yichun Wang

“…The unique hexagonal‐close‐packed geometry of iCC structure enables HCHTS through conventional plate reader analysis and fluorescent microscopy assisted by house‐developed automated data processing algorithm. This advancement offers promising applications in tissue engineering, disease modeling, and drug development in biomedical research.…”
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Multimodal Approach (MRI and Ultrasonography) to the Diagnosis of Fetal Congenital Heart Diseases by A. V. Pomortsev, M. N. Karakhalis, N. V. Krivonosova, K. F. Goloseev

“…In 85.7% of the fetuses, the findings of different imaging techniques fully coincided with the autopsy findings.Conclusions: In this cohort of pregnant women, the second screening should include more examinations to verify the diagnosis of CHD. …”
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A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes by Shuheng Yang, Ralf Weiskirchen, Wenjing Zheng, Xiangxu Hu, Aibiao Zou, Zhiguo Liu, Hualin Wang

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A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach by Paola Argiento, Anna D'Agostino, Rossana Castaldo, Monica Franzese, Matteo Mazzola, Ekkehard Grünig, Lavinia Saldamarco, Valeria Valente, Alessandra Schiavo, Erica Maffei, Davide Lepre, Antonio Cittadini, Eduardo Bossone, Michele D'Alto, Luna Gargani, Alberto Maria Marra

“…Conclusions: The PH-targeted ML models could streamline routine screening for PH, facilitating earlier identification and better RHC referrals.…”
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HPRNA: Predicting synergistic drug combinations for angina pectoris based on human pathway relationship network algorithm. by Mengyao Zhou, Mengfan Xu, Xiangling Zhang, Xiaochun Xing, Yang Li, Guanghui Wang, Guiying Yan

“…Compared to lengthy medical drugs experimental screening, mathematical models and algorithms show great potential in synergistic drug combinations prediction. …”
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Integrated Machine Learning Algorithms-Enhanced Predication for Cervical Cancer from Mass Spectrometry-Based Proteomics Data by Da Zhang, Lihong Zhao, Bo Guo, Aihong Guo, Jiangbo Ding, Dongdong Tong, Bingju Wang, Zhangjian Zhou

“…Furthermore, by integrating feature importance values, Shapley values, and local interpretable model-agnostic explanation (LIME) values, we demonstrated that the diagnostic area under the curve (AUC) achieved by our multi-dimensional learning models approached 1, significantly outperforming the diagnostic AUC of single markers derived from the PRIDE database. …”
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Identification of Plasma Proteins Associated with Alzheimer's Disease Using Feature Selection Techniques and Machine Learning Algorithms by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…This study aims to use computational algorithms to explore the relationship between plasma proteins and AD progression by identifying a panel of plasma proteins that can serve as biomarkers for tracking and diagnosing AD. …”
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Improving routine mental health screening for depression and anxiety in a paediatric lupus clinic: a quality improvement initiative for enhanced mental healthcare by Deborah M Levy, Evelyn Smith, Lawrence Ng, Andrea M Knight, Linda Hiraki, Tala El Tal, Avery Longmore, Audrea Chen, Holly Convery, Dinah Finkelstein, Chetana Kulkarni, Neely Lerman, Karen Leslie, Sharon Lorber, Oscar Mwizerwa, Vandana Rawal, Stephanie Wong, Asha Jeyanathan

“…Statistical process control charts were used to analyse the outcome measure for percentage of screened patients with cSLE. Patient and caregiver satisfaction surveys were conducted at baseline and after screening as a balancing measure.Interventions MH screening workflow with a referral algorithm was developed with stakeholders. …”
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Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation by Tatsuki Hasegawa, Hayato Kizaki, Keisho Ikegami, Shungo Imai, Yuki Yanagisawa, Shuntaro Yada, Eiji Aramaki, Satoko Hori

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Genetics, sex and the use of platelet‐rich plasma influence the development of arthrofibrosis after anterior cruciate ligament reconstruction by Mikel Sánchez, Izarbe Yarza, Cristina Jorquera, Jose María Aznar, Leonor López deDicastillo, Cristina Valente, Renato Andrade, João Espregueira‐Mendes, David Celorrio, Beatriz Aizpurua, Juan Azofra, Diego Delgado

“…Abstract Purpose To identify genes and patient factors that are related to the development of arthrofibrosis in patients after anterior cruciate ligament (ACL) reconstruction and to develop a prognostic model. Methods The study included patients diagnosed with ACL injury who underwent ACL reconstruction. …”
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Economic evaluation of a novel genetic screening test for risk of venous thromboembolism compared with standard of care in women considering combined hormonal contraception in Swit... by Zanfina Ademi, C Simone Sutherland, Matthias Schwenkglenks, Nadine Schur, Joëlle Michaud, Myriam Lingg, Arjun Bhadhuri, Thierry D. Pache, Johannes Bitzer, Pierre Suchon, Valerie Albert, Kurt E. Hersberger, Goranka Tanackovic

“…The risk of having a VTE was derived from the risk algorithm that underpins the PP test. The remaining model inputs relating to population characteristics, costs, health resource use, mortality and utilities were derived from published studies or national sources. …”
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Estimation of Canopy Water Content by Integrating Hyperspectral and Thermal Imagery in Winter Wheat Fields by Chenkai Gao, Shuimiao Liu, Pengnian Wu, Yanli Wang, Ke Wu, Lingyun Li, Jinghui Wang, Shilong Liu, Peimeng Gao, Zhiheng Zhao, Jing Shao, Haolin Yu, Xiaokang Guan, Tongchao Wang, Pengfei Wen

“…</b> Ultimately, the CWC prediction model of winter wheat hyperspectral characteristic bands and thermal imaging information fusion was created using the GRA algorithm. …”
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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

“…The control experiment reduced image preparation time from 10 hours for manual cropping of 900 photos to 30 seconds with the automated model. Downstream strabismus screening task validation showed our model (with head tilt correction) achieving an area under the curve of 0.917 (95% CI 0.901‐0.933), surpassing Dlib-toolkit and faster R-CNN (both without head tilt correction) with an area under the curve of 0.856 (PP ConclusionsThis study delivers an AI-driven platform featuring a preprocessing algorithm that automates eye region cropping, correcting head tilt variations to improve image quality for AI development and clinical use. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Although more data were available to populate the screening population model, there was substantial uncertainty across all models. …”
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Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci by Jie Lu, Xinhao Lu, Yixiao Wang, Hengdong Zhang, Lei Han, Baoli Zhu, Boshen Wang

“…The SNP loci screened by these models are pivotal in the process of NIHL prediction, which further improves the prediction accuracy of the model. …”
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Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study by Chengkun Sun, Erin Mobley, Michael Quillen, Max Parker, Meghan Daly, Rui Wang, Isabela Visintin, Ziad Awad, Jennifer Fishe, Alexander Parker, Thomas George, Jiang Bian, Jie Xu

“…Given the distinct pathology of colon cancer (CC) and rectal cancer (RC), we created separate prediction models for each cancer type with various ML algorithms. …”
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Feature Selection based on Genetic Algorithm for Classification of Mammogram Using K-means, k-NN and Euclidean Distance by Kameran Adil Ibrahim

“…., the classifications was done on the bases of the features selected using genetic algorithm. Attempts have also been made to study the performance of each feature selected by Genetic Algorithm (GA) in classification. …”
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