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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Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

“…This study introduces a hybrid feature selection method based on genetic algorithm (GA) and Bucket of Models (BoM) approach to improve breast cancer detection and classification. …”
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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 Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing by Jiayuan Shen, Bing Han, Yang Li, Zongxu Pan, Di Yin, Yugang Feng, Guangzuo Li

“…We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. …”
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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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Data transmission algorithm for mobile wireless sensor network based on power loss equalization control mechanism by Lijun LI, Fuquan ZHANG, Hongfei LIU

“…In order to solve the problem of synchronization addressing and the inadequacy of power interaction among nodes in the current mobile wireless sensor network,a new data transmission algorithm for mobile wireless sensor network was proposed.Firstly,the broadcast mechanism was adopted to realize synchronous control packet transmission and reduce the pressure caused by the synchronization flow to the addressing process.Then regional node flow valve control mechanism was used,and data traffic between sink nodes and regional node links were recorded and got by interception,flow link equalization was further adopted to promote traffic equalization.in the further step.Finally,the limited bandwidth based on wheel number-sink link jitter screening mode could be identified,and the transmission failure due to limited bandwidth was reduced.Simulation results show that compared with the bandwidth of the root zone node and widely used in limiting transmission algorithm,node link stability encoding algorithm and hierarchical encoding algorithm,the data transmission bandwidth can be improved,the packet loss rate can be reduced,and the practical needs can be better met.…”
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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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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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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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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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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 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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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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Cancer patients' experiences with and opinions on the process 'Screening of Distress and Referral Need' (SDRN) in clinical practice: A quantitative observational clinical study. by Floor M van Nuenen, Stacey M Donofrio, Harry B M van de Wiel, Josette E H M Hoekstra-Weebers

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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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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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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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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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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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