CPO-VMD Combined With Multiscale Permutation Entropy for Noise Reduction in GNSS Vertical Time Series in Mining Areas by Xu Yang, Xinxin Yao, Xinjian Fang, Xuexiang Yu, Yi Wu, Shicheng Xie

“…Taken together, the CPO-VMD-MPE method proposed in this paper significantly reduces the noise in the time series and provides a better theoretical and methodological reference for deformation analysis and prediction.…”
Get full text

Identification and validation of a prognostic risk model based on radiosensitivity-related genes in nasopharyngeal carcinoma by Yi Li, Xinyi Hong, Wenqian Xu, Jinhong Guo, Yongyuan Su, Haolan Li, Yingjie Xie, Xing Chen, Xiong Zheng, Sufang Qiu

“…This study aims to identify radiosensitivity-related genes in NPC and develop a prognostic model to predict patient outcomes. Methods: We analyzed 179 NPC samples from Fujian Cancer Hospital using RNA sequencing. …”
Get full text

Unveiling ac4C modification pattern: a prospective target for improving the response to immunotherapeutic strategies in melanoma by Jianlan Liu, Pengpeng Zhang, Chaoqin Wu, Binlin Luo, Xiaojian Cao, Jian Tang

“…We developed and confirmed an excellent acRG-related signature (acRGS) utilizing a comprehensive set of 101 algorithm combinations derived from 10 machine learning algorithms. …”
Get full text

Towards accurate L4 ocean colour products: Interpolating remote sensing reflectance via DINEOF by Christian Marchese, Simone Colella, Vittorio Ernesto Brando, Maria Laura Zoffoli, Gianluca Volpe

“…Our outcomes show that this “upstream interpolation” method can generate a consistent Rrs dataset, thereby improving the accuracy of L4 Chl predictions when used as input in algorithms for remote Chl estimation. …”
Get full text

Automatic Selection of Machine Learning Models for Armed People Identification by Alonso Javier Amado-Garfias, Santiago Enrique Conant-Pablos, Jose Carlos Ortiz-Bayliss, Hugo Terashima-Marin

“…These models use 20 predictors to make their predictions. These predictors are computed from the bounding box coordinates of the detected people and weapons, their distances, and areas of intersection. …”
Get full text

Development and Testing a New Online Dynamic Nomogram for Contrast-Induced Acute Kidney Injury in Elderly Patients with ST-Segment Elevation Myocardial Infarction by Jin J, Ding J, Zhang X, Wang L, Zhang X, Li W, Li S

“…Lasso regression selected predictors, and nine Machine Learning (ML) algorithms were evaluated via Receiver Operating Characteristic (ROC) analysis. …”
Get full text

Critical gene network and signaling pathway analysis of the extracellular signal-regulated kinase (ERK) pathway in ischemic stroke by Rui Mao, Lei Wang, Haitao Zhang, Jiaojiao Gong, Hua Liu

“…Four machine learning algorithms (Boruta, SVM, LASSO, random forest) corroborated hub gene robustness. …”
Get full text

Nasolacrimal Duct Obstruction Secondary to Radioactive Iodine-131 Therapy for Differentiated Thyroid Cancer by A. A. Trukhin, V. D. Yartsev, M. S. Sheremeta, D. V. Yudakov, M. O. Korchagina, R. Kh. Salimkhanov, S. V. Grishkov

“…The authors have developed a new method for predicting secondary NLDO by a combination of the patient’s individual parameters and treatment plan; the identified predictors help to personalise radioiodine therapy. …”
Get full text

MMLT: Efficient object tracking through machine learning-based meta-learning by Bibek Das, Asfak Ali, Suvojit Acharjee, Jaroslav Frnda, Sheli Sinha Chaudhuri

“…The proposed hybrid model refines predictions from traditional tracking methods using machine learning to enhance performance. …”
Get full text

Integrative Analysis of Neutrophil-Associated Genes Reveals Prognostic Significance and Immune Microenvironment Modulation in Cervical Cancer by Ting Hu, Haijing Wu, Xinghan Cheng, Haoyue Gao, Min Yang

“…High-risk patients exhibited an immunosuppressive tumor microenvironment, elevated TIDE scores, and lower predicted responsiveness to immunotherapy. SEMA6B was significantly downregulated in the tumour group but may be reactivated during metastasis. …”
Get full text

Develoment of The Computer Simulation of Oscillation in Physics Learning by Y Sumardi, A F Amalia, U N Prabowo

“…The use of simulations within teaching process had a positive impact on students’ being able to predict and explain the phenomena. It also designed to provide possibility to explore physics phenomenon which cannot be realized in school conditions.  …”
Get full text

Host Circulating Immunometabolism-Associated Biomarkers for Early Diagnosis of Active Tuberculosis: Multi-Omics Screening with Experimental Validation by Yang Z, Dong Y, Shang Y, Li H, Ren W, Li S, Pang Y

“…A nomogram was constructed to comprehensively predict the risk of active TB. Mechanistically, protein–protein interactions and gene set enrichment analysis revealed that four hub genes affected pteridine and lipid metabolism and were associated with the innate immune pathways. …”
Get full text

Treatment of infections in young infants in low- and middle-income countries: a systematic review and meta-analysis of frontline health worker diagnosis and antibiotic access. by Anne C C Lee, Aruna Chandran, Hadley K Herbert, Naoko Kozuki, Perry Markell, Rashed Shah, Harry Campbell, Igor Rudan, Abdullah H Baqui

“…For study question 1, meta-analysis showed that clinical sign-based algorithms predicted bacterial infection in young infants with high sensitivity (87%, 95% CI 82%-91%) and lower specificity (62%, 95% CI 48%-75%) (six studies, n = 14,254). …”
Get full text

Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium by Kun Gao, Zhenyu Huang, Zhouwei Liao, Yanfei Wang, Dayu Chen

“…We employed several machine learning algorithms, including least absolute shrinkage and selection operator and support vector machine–recursive feature elimination, to screen for key genes. …”
Get full text

RISKS OF IMPLEMENTING AND USING ARTIFICIAL INTELLIGENCE BY OIL AND GAS SECTOR ENTERPRISES by V.B. Kochkodan, M.Yu. Petryna

“…Scenario modeling tools were applied to predict the potential consequences of risk realization.A systematic approach was applied to assess the risk levels of using AI technologies in oil and gas enterprises. …”
Get full text

Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4 by Baohua Zhu, Ziyang Mo, Yi Bao, Xinxin Gan, Linhui Wang

“…The LASSO + RSF combination model performed best, and the model could accurately predict patient prognosis. The survival of patients in the high-risk group was significantly worse than that in the low-risk group. …”
Get full text

Wide-angle deep ultraviolet antireflective multilayers via discrete-to-continuous optimization by Kim Jae-Hyun, Kim Dong In, Lee Sun Sook, An Ki-Seok, Yim Soonmin, Lee Eungkyu, Kim Sun-Kyung

“…To date, various optimization algorithms have been used to design non-intuitive photonic structures with unconventional optical performance. …”
Get full text

Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis. by Shang-Ming Zhou, Fabiola Fernandez-Gutierrez, Jonathan Kennedy, Roxanne Cooksey, Mark Atkinson, Spiros Denaxas, Stefan Siebert, William G Dixon, Terence W O'Neill, Ernest Choy, Cathie Sudlow, UK Biobank Follow-up and Outcomes Group, Sinead Brophy

“…<h4>Objectives</h4>1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs.…”
Get full text

Multi-omics analysis of the effects of pla2g4a on the prognosis of various cancers and its experimental validation in breast cancer cell lines by Yao Qian, Quan Yuan, Hao Yu, Rongjie Ye, Ming Niu, Feng Liu

“…The function of PLA2G4A in BC was validated through experiments, and its drug response and molecular docking were predicted using various databases and software tools. …”
Get full text

Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…We developed custom transfer parameters by attempting to predict geomorphon-based landforms using a large dataset of digital terrain data provided by the United States Geological Survey’s 3D Elevation Program (3DEP). …”
Get full text