Prognostic and Diagnostic Value of Spontaneous Tumor-Related Antibodies by Sebastian Kobold, Tim Luetkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic

“…There is an urgent need for earlier diagnosis of malignancies and more stringent monitoring of relapses after antitumor therapy. …”
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Potential Metabolic Markers in the Tongue Coating of Chronic Gastritis Patients for Distinguishing Between Cold Dampness Pattern and Damp Heat Pattern in Traditional Chinese Medici... by Yuan S, Zhang R, Zhu Z, Zhou X, Zhang H, Li X, Hao Y

“…We applied metabolomics to identify differential metabolites distinguishing these patterns.Methods: In this study, the first principal component was analyzed by the OPLS-DA model. The model quality was evaluated by 7-fold cross-validation, and the model validity was evaluated based on R²Y (interpretability of categorical variable Y) and Q² (predictability of the model), and the permutation test was used for further verification. …”
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Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning by Nanding Li, Naoshi Kondo, Yuichi Ogawa, Keiichiro Shiraga, Mizuki Shibasaki, Daniele Pinna, Moriyuki Fukushima, Shinichi Nagaoka, Tateshi Fujiura, Xuehong De, Tetsuhito Suzuki

“…This study developed a handheld camera system capable of capturing cattle fundus images and predicting vitamin A levels in real time using deep learning. 4000 fundus images from 50 Japanese Black cattle were used to train and test the prediction algorithms, and the model achieved an average 87%, 83%, and 80% accuracy for three levels of vitamin A deficiency classification (particularly 87% for severe level), demonstrating the effectiveness of camera system in vitamin A deficiency prediction, especially for screening and early warning. …”
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From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer’s Disease and Other Neurological Disorders by Mashael A. Alghamdi

“…Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. …”
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Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems by Natalya Denissova, Serik Nurakynov, Olga Petrova, Daniker Chepashev, Gulzhan Daumova, Alena Yelisseyeva

“…The analysis involved screening relevant studies on remote sensing, avalanche dynamics, and data processing techniques. …”
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AI-Powered Synthesis of Structured Multimodal Breast Ultrasound Reports Integrating Radiologist Annotations and Deep Learning Analysis by Khadija Azhar, Byoung-Dai Lee, Shi Sub Byon, Kyu Ran Cho, Sung Eun Song

“…Our method synthesizes comprehensive breast US reports by combining the extracted information from radiologists’ annotations during routine screenings with the analysis results from deep learning algorithms on multimodal US images. …”
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Smart driving assistance system for mining operations in foggy environments by Swades Kumar Chaulya, Monika Choudhary, Naresh Kumar, Vikash Kumar, Abhishek Chowdhury

“…In image processing under dense fog where visibility is below 5 m, typical performance standards are around 0.9 for contrast, above 0.5 for structural similarity index measure, over 20 dB for peak signal-to-noise ratio, over 0.5 for visual information fidelity, and more than 0.5 for universal quality index. Thus, the test results indicate that the proposed image enhancement algorithm produced significantly improved images, proving its effectiveness in extremely low visibility situations. …”
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Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy by Hassan H. Alhassan

“…Among all models, the Random Forest (RF) algorithm had the best prediction accuracy, with a value of 0.6832 on the test set and 0.7432 on the training set, and was employed to screen the target library of 11,032 phytochemicals. …”
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A method for the identification of lactate metabolism-related prognostic biomarkers and its validations in non-small cell lung cancer by Weiyang Yang, Miao Gu, Yabin Zhang, Yunfan Zhang, Tao Liu, Di Wu, Juntao Deng, Min Liu, Youwei Zhang

“…The existing methods for the construction of prognosis prediction models are mostly based on single models such as linear models, SVM, and decision trees. …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. Background: The standard diagnostic criteria tools for FH require GT. …”
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RAD-Seq-derived SSR markers: a new paradigm for genetic analysis and construction of genetically improved production populations in Pinus koraiensis by Pingyu Yan, Wanying Zhang, Junfei Hao, Xiaotian Miao, Jun Wu, Zixiong Xie, Zhixin Li, Lei Zhang, Hanguo Zhang

“…A production population of 20 individuals was constructed via the simulated annealing algorithm, which exhibited a more reasonable mating system (F=−0.028) and demonstrated superior cone production compared with that of the plus tree population, with an increase of 79.6%. …”
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Sleepiness, fatigue, anxiety and depression in Chronic Obstructive Pulmonary Disease and Obstructive Sleep Apnea - Overlap - Syndrome, before and after continuous positive airways... by Nicholas-Tiberio Economou, Ioannis Ilias, Lemonia Velentza, Yiannis Papachatzakis, Paul Zarogoulidis, Anastasios Kallianos, Georgia Trakada

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Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer by Miao Ao, You Wu, Kunyu Wang, Haixia Luo, Wei Mao, Anqi Zhao, Xiaomeng Su, Yan Song, Bin Li

“…After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. …”
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The impact of specialised gastroenterology services for pelvic radiation disease (PRD): Results from the prospective multi-centre EAGLE study. by John N Staffurth, Stephanie Sivell, Elin Baddeley, Sam Ahmedzai, H Jervoise Andreyev, Susan Campbell, Damian J J Farnell, Catherine Ferguson, John Green, Ann Muls, Raymond O'Shea, Sara Pickett, Lesley Smith, Sophia Taylor, Annmarie Nelson

“…All men completed a validated screening tool for late bowel effects (ALERT-B) and the Gastrointestinal Symptom Rating Score (GSRS); men with a positive score on ALERT-B were offered management following a peer reviewed algorithm for pelvic radiation disease (PRD). …”
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Research on Feature Extraction of Performance Degradation for Flexible Material R2R Processing Roller Based on PCA by Yaohua Deng, Huiqiao Zhou, Kexing Yao, Zhiqi Huang, Chengwang Guo

“…The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. …”
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A machine learning approach to predict positive coronary artery calcium scores in individuals with diabetes: a cross-sectional analysis of ELSA-Brasil baseline data by J.L. Amorim, I.M. Bensenor, A.P. Alencar, A.C. Pereira, A.C. Goulart, P.A. Lotufo, I.S. Santos

“…We analyzed 25 sociodemographic, medical history, symptom-related, and laboratory variables from 585 participants from the São Paulo investigation center with CACS data and no overt cardiovascular disease at baseline. We used six ML algorithms to build models to identify individuals with positive CACS. …”
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GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Subsequently, a two-stage suppression model based on robust estimation theory is developed to effectively suppress interference. …”
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Time-Distributed Vision Transformer Stacked With Transformer for Heart Failure Detection Based on Echocardiography Video by Mgs M. Luthfi Ramadhan, Adyatma W. A. Nugraha Yudha, Muhammad Febrian Rachmadi, Kevin Moses Hanky Jr Tandayu, Lies Dina Liastuti, Wisnu Jatmiko

“…This study proposed a novel deep learning model consisting of a time-distributed vision transformer stacked with a transformer. …”
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Biomarker-driven drug repurposing for NAFLD-associated hepatocellular carcinoma using machine learning integrated ensemble feature selection by Subhajit Ghosh, Sukhen Das Mandal, Subarna Thakur

“…The incidence of non-alcoholic fatty liver disease (NAFLD), encompassing the more severe non-alcoholic steatohepatitis (NASH), is rising alongside the surges in diabetes and obesity. …”
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Cross-validation of the safe supplement screener (S3) predicting consistent third-party-tested nutritional supplement use in NCAA Division I athletes by Kinta D. Schott, Avaani Bhalla, Emma Armstrong, Ryan G. N. Seltzer, Floris C. Wardenaar

“…IntroductionThis cross-sectional study aimed to cross-validate an earlier developed algorithm-based screener and explore additional potential predictors for whether athletes will use third-party-tested (TPT) supplements.MethodsTo justify the initial model behind the supplement safety screener (S3) algorithm which predicts whether athletes will use TPT supplements, a cross-validation was performed using this independent dataset based on responses of a large group of collegiate NCAA DI athletes. …”
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