Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…A network meta-analysis of diagnostic test and Thakkinstian’s algorithm were used to select the most appropriate genetic model, along with false-positive report probability (FPRP) for noteworthy associations. …”
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Integrating taxonomic and phenotypic information through FISH-enhanced flow cytometry for microbial community dynamics analysis by Valérie Mattelin, Josefien Van Landuyt, Frederiek-Maarten Kerkhof, Yorick Minnebo, Nico Boon

“…As a reference to correlate increased distinction with the incorporation of taxonomic information, 16S rRNA gene sequencing was used. Finally, a predictive algorithm was trained to correctly classify samples in the differently treated groups. …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…By implementing the XGBoost algorithm, we established predictive models for defect rate quantification (regression) and defect grade classification. …”
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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

“…., k-nearest neighbor (KNN), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were combined with various molecular fingerprints (MACCS and Morgan2) to develop multiple predictive models. Among these models, the RF algorithm coupled with the MACCS fingerprint emerged as the best performing model. …”
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Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA by Runqing Tan, Song Zhou, Min Sun, Yu Liu, Xiumei Ni, Jin He, Gang Guo, Kaiyun Liu

“…The artificial neural network linked genetic algorithm (ANN-GA) model exhibited superior predictive accuracy, achieving a rHpaA yield of 0.61 g/L, which represents a 93.2% increase compared to the initial medium. …”
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Flood-tech frontiers: smart but just? A systematic review of AI-driven urban flood adaptation and  associated governance challenges by Johannes Bhanye

“…In recent years, Artificial Intelligence (AI) has gained attention as a promising solution in flood risk management, offering capabilities in real-time prediction, risk assessment, decision support, and community engagement. …”
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Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. …”
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Prognostic value of gene signatures and proliferation in lymph-node-negative breast cancer. by Kristin Jonsdottir, Jörg Assmus, Aida Slewa, Einar Gudlaugsson, Ivar Skaland, Jan P A Baak, Emiel A M Janssen

“…<h4>Introduction</h4>The overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…The prognostic model incorporating these five genes demonstrated robust predictive power in both training and validation cohorts. …”
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Challenges, Difficulties, and Delayed Diagnosis of Multiple Myeloma by Tugba Zorlu, Merve Apaydin Kayer, Nazik Okumus, Turgay Ulaş, Mehmet Sinan Dal, Fevzi Altuntas

“…<b>Conclusions:</b> Multimodal tools for early diagnosis of MM. Educational campaigns to raise awareness of the disease, algorithms dedicated to routine care and novel technologies, including AI and big data analytics, and new biomarkers may serve this purpose, as well as genomic approaches to the premalignant MGUS stage.…”
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Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare by Jeremy Y. Ng, Holger Cramer, Myeong Soo Lee, David Moher

“…AI may augment TCIM by assisting in early disease detection, providing personalized treatment plans, predicting health trends, and enhancing patient engagement. …”
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Transferring Face Recognition Techniques to Entomology: An ArcFace and ResNet Approach for Improving Dragonfly Classification by Zhong Li, Shaoyan Pu, Jingsheng Lu, Ruibin Song, Haomiao Zhang, Xuemei Lu, Yanan Wang

“…The model is mainly built based on the classic face recognition algorithm (ResNet50+ArcFace), and ResNet50 is used as the comparison algorithm for model performance. …”
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Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin by Fei Tian, Wenhao Zheng, Aosai Zhao, Jingyue Liu, Yunchen Liu, Hui Zhou, Wenjing Cao

“…This model incorporates select seismic attributes and leverages fusion algorithms like K-means, ellipsoid growth, and wavelet transformations. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. …”
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Advancing Alzheimer's Therapy: Computational strategies and treatment innovations by Jibon Kumar Paul, Abbeha Malik, Mahir Azmal, Tooba Gulzar, Muhammad Talal Rahim Afghan, Omar Faruk Talukder, Samar Shahzadi, Ajit Ghosh

“…Moreover, machine learning algorithms enhance early diagnosis and enable precision medicine strategies by analyzing multi-modal datasets. …”
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Identification and multi-omics analysis of essential coding and long non-coding genes in colorectal cancer by Yanguo Li, Zixing Meng, Chengjiang Fan, Hao Rong, Yang Xi, Qi Liao

“…Then, 29 essential long non-coding genes (ESLs) were predicted using Hypergeometric Test (HT) and Personalized PageRank (PPR) algorithms based on ESPs and co-expressed network constructed from scRNA-seq. …”
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3D Reconstruction and Deformation Detection of Rescue Shaft Based on RGB-D Camera by Hairong Gu, Bokai Liu, Lishun Sun, Mostak Ahamed, Jia Luo

“…Experimental results demonstrate the superiority of the Speeded Up Robust Features (SURF) algorithm in feature extraction and the effectiveness of the Random Sample Consensus (RANSAC) algorithm in filtering mismatched points. …”
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A Resting ECG Screening Protocol Improved with Artificial Intelligence for the Early Detection of Cardiovascular Risk in Athletes by Luiza Camelia Nechita, Dana Tutunaru, Aurel Nechita, Andreea Elena Voipan, Daniel Voipan, Anca Mirela Ionescu, Teodora Simina Drăgoiu, Carmina Liana Musat

“…<b>Methods:</b> For each of the six sports, resting 12-lead ECGs from healthy children and junior athletes were analyzed using AI algorithms trained on annotated datasets. Parameters included the QTc intervals, PR intervals, and QRS duration. …”
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Literature Review of Prognostic Factors in Secondary Generalized Peritonitis by Valerii Luțenco, Adrian Beznea, Raul Mihailov, George Țocu, Verginia Luțenco, Oana Mariana Mihailov, Mihaela Patriciu, Grigore Pascaru, Liliana Baroiu

“…Emerging evidence suggests that machine learning algorithms may improve early risk stratification and individualized outcome prediction when integrated with conventional scoring systems. …”
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Inflammation-Mediated Regulation of MicroRNA Expression in Transplanted Pancreatic Islets by Valia Bravo-Egana, Samuel Rosero, Dagmar Klein, Zhijie Jiang, Nancy Vargas, Nicholas Tsinoremas, Marco Doni, Michele Podetta, Camillo Ricordi, R. Damaris Molano, Antonello Pileggi, Ricardo L. Pastori

“…The association between these miRNAs and mRNA target-predicting algorithms in genome-wide RNA studies of β-cell inflammation identified 238 potential miRNA gene targets. …”
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