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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Harnessing routine MRI for the early screening of Parkinson’s disease: a multicenter machine learning study using T2-weighted FLAIR imaging by Junyan Fu, Hongyi Chen, Chengling Xu, Zhongzheng Jia, Qingqing Lu, Haiyan Zhang, Yue Hu, Kun Lv, Jun Zhang, Daoying Geng

“…Critical relevance statement Our study confirmed that early screening of Parkinson’s Disease based on the conventional T2W FLAIR images was feasible with the aid of machine learning algorithms in a large multicenter cohort and those models had certain generalization. …”
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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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LPCF-YOLO: A YOLO-Based Lightweight Algorithm for Pedestrian Anomaly Detection with Parallel Cross-Fusion by Peiyi Jia, Hu Sheng, Shijie Jia

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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…The qSepsis was derived by three ML algorithms, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). …”
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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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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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Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation by Hutan Ashrafian, Jessica Morley, Joe Zhang, Christopher Oddy

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A New Fast Sparse Unmixing Algorithm Based on Adaptive Spectral Library Pruning and Nesterov Optimization by Kewen Qu, Fangzhou Luo, Huiyang Wang, Wenxing Bao

“…To address these shortcomings, this article proposes a new fast two-step sparse unmixing algorithm, called NeSU-LP, which is based on adaptive spectral library pruning technology and the Nesterov fast optimization strategy. …”
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SARS-CoV-2 Prediction Strategy Based on Classification Algorithms from a Full Blood Examination by C. F. Choukhan, I. Lasri, R. El Hatimi, M. R. Lemnaouar, M. Esghir

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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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Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model by Chongyuan Wang, Huiyi Liu

“…The Dendritic Neuron Model (DNM) offers a more realistic alternative by simulating nonlinear and compartmentalized processing within dendritic branches, enabling efficient and transparent learning. …”
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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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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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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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Application of Convolutional Neural Network (CNN) Algorithm with ResNet-101 Architecture for Monkey Pox Detection in Human by Al Fathir Rizal Januar, Jamaludin Indra, Dwi Sulistya Kusumaningrum, Sutan Faisal

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Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures by Timo F.W. Soeterik, Xiaobo Wu, Roderick C.N. Van den Bergh, Claudia Kesch, Fabio Zattoni, Ugo Falagario, Alberto Martini, Marcin Miszczyk, Vittorio Fasulo, Martina Maggi, Veeru Kasivisvanathan, Pawel Rajwa, Giancarlo Marra, Giorgio Gandaglia, Peter K.F. Chiu

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Chemoreactome screening of aquacobalamin and heptamethyl ester of cyanoaquacobyrinic acid cytotoxic effects on tumor cells with experimental confirmation on BT-474 and A549 cell by I. Yu. Torshin, M. V. Filimonova, O. A. Gromova, L. A. Maiorova, M. A. Sorokina, D. E. Frolova, A. N. Gromov, I. A. Reyer

“…Experimental studies of tumor cell cultures were carried out using the MTT testwith aquacobalamin and HECСA on cell lines of immortalized (telomerized) fibroblasts (Fb-hTERT), lung carcinoma (A549), and breast duct cancer (BT-474).Results. Chemoreactome screening of the effects of molecules on tumor cells made it possible to obtain estimates of cell growth IC50 for 470 tumor cell lines. …”
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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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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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