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Monthly Biological Variation of Five Lung Cancer Markers in Healthy Older Individuals: Evidence from Combined Prospective Cohort and Real-World Data Analyses 🌷doi.org/10.3343/alm.2025.052… Ann Lab Med. February 12, 2026. Ziyang Han #BayesianModel #LungCancer #TumorBiomarkers
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A Bayesian joint bivariate longitudinal model examines structure-function relationships in glaucoma. New paper outlines slope estimation and prediction accuracy vs. SLR, supporting better monitoring of disease progression. #glaucoma #BayesianModel ow.ly/ZFYr50WyIqf
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22 Jul 2025
šŸ“Š Exploring Bayesian Techniques in Algorithmic Trading Bayesian methods provide a framework in which probabilities are updated as new information becomes available, making them particularly relevant for evolving financial systems. This project outlines how such techniques were applied to trading-related tasks involving price prediction, parameter adaptation, and risk evaluation. šŸ” Project Highlights • Built two deep learning models to forecast open prices of the Bank Nifty index and its top five constituents • Used 21 months of 1-minute data and 20 years of daily data for training/testing • Integrated techniques such as SMOTE for class imbalance and XGBoost for feature ranking • Applied Keras callbacks (EarlyStopping, ModelCheckpoint) to address overfitting • Focused on consensus-based signals, where both models must agree before executing trades • Managed minute-level and daily datasets using a MySQL database 🧠 Tools and Techniques Used TensorFlow & Keras Scikit-learn, XGBoost, TA-Lib SMOTE (Imbalanced-learn) Feature engineering with RSI, MFI, ATR, Bollinger Bands, and more Read the full guide with the entire project here: blog.quantinsti.com/introduc… šŸ“š For readers interested in related topics: Quant Roles Overview: quantinsti.com/quant-roles Quantitative Trader: quantinsti.com/articles/quan… Quant Analyst & Researcher: quantinsti.com/articles/quan… Quant Developer: quantinsti.com/quant-roles/q… Risk Analyst: quantinsti.com/articles/risk… šŸ”— Learn more about the EPAT programme: quantinsti.com/epat šŸ“£ šŸ”“ Detailed EPAT Walkthrough & AMA | Live Webinar Join us for a dedicated session exploring the Executive Programme in Algorithmic Trading (EPAT). Get a comprehensive overview of the 6-month journey, support offered, alumni success, and post-programme career services. The session concludes with a live Q&A. šŸ—“ļø Thursday, July 24, 2025 šŸ•— 8:30 AM EST | 6:30 PM IST | 9:00 PM SGT šŸŽ¤ Speaker: Rohan Mathews, Global Business Head – QuantInsti šŸ”— Register: quantinsti.com/epat #QuantInsti #EPAT #AlgorithmicTrading #QuantRoles #DeepLearning #PythonForFinance #BayesianModel #TradingSystems #FinancialData #Backtesting #QuantitativeFinance #FeatureEngineering
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Out Now! Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain bit.ly/3RR64eE #Microbiology #Microbiome #BayesianModel
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Bayesian Approach Enhances Understanding and Prediction of Leishmania Disease - scft.link/vXIMV Dr. Felix Pabon-Rodriguez from Indiana University School of Medicine and his team developed a Bayesian joint model to better understand and predict Leishmania disease progression. The research, published in PLOS ONE, integrates longitudinal data and time-to-event data to explore the interactions between pathogen load, immune responses, and disease outcomes. #BayesianModel #LeishmaniaResearch #InfectiousDisease #Biostatistics #ImmuneResponse #sciencefeatured #sciencenews
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27 Apr 2024
JM! Don't miss the opportunity to read the #originalarticle, #openaccess ā€œAllergen #immunotherapy in #MASK-air users in real-life: Results of a #Bayesian mixed-effects modelā€ published in the #CTA_Journal. Here šŸ”— onlinelibrary.wiley.com/doi/… #allergen #MASKair #Bayesianmodel
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Boosting sea state forecasts for the Aran Islands! This study combines local-scale forecasts and Bayesian Model Averaging to improve accuracy by 1-8%. An accessible method for anyone reliant on precise sea state predictions, with minimal computational power needed. šŸŒŠāš”ļø Tatjana Kokina (@koksikt), Daniel Santiago PelĆ”ez-Zapata, Thomas Brendan Murphy & FrĆ©dĆ©ric Dias (@FredericDiasUCD) @CentreBorelli -> doi.org/10.1017/eds.2023.31 #seastateforecast #BayesianModel #waves #wavestatistics #weatherprediction #Aran
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New experiment: launching my @topmateHQ page today, where you can book a 1:1 call or ask any queries you may have. Whether you need help with a #BayesianModel, are looking for a #StatsModeling mentor, or even wanna chat on #GoingNomad -- I'm available! Best Bayesian wishes šŸ––
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6. Bayesian Model Bayesian Model Selection is a method of comparing the relative likelihoods of different hypotheses given the data and selecting the hypothesis with the highest likelihood. @hashnode @WeMakeDevs #bayesianmodel
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Variational inference uses optimization, rather than integration, to approximate the marginal likelihood, and thereby the posterior, in a Bayesianmodel. šŸ“„ arxiv.org/abs/2301.01236v1
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Research Fellow @Chigedson is @RSSAnnualConf presenting our new national #immunisation coverage methodology Background on this @WHO and @UNICEF funded #ZeroDose project: worldpop.org/current-project… #StatsMethods #BayesianModel
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21 Jul 2022
The #originalarticle ā€œ#Allergenimmunotherapy in #MASK-air users in real-life: Results of a Bayesian mixed-effects modelā€ published in the #CTA_Journal is available and #openaccess! šŸ”—Link: onlinelibrary.wiley.com/doi/… #allergen #bayesianmodel

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6 Jun 2022
A new Statistical Report in @ESAEcology: Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities doi.org/10.1002/ecy.3769 With #OpenData in @figshare @IBAHCM @__Biodiversity @CrinanJarrett #PopulationSize #BayesianModel
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scCODA is a Bayesian model for compositional single-cell data analysis. #scRNAseq #DataAnalysis #BayesianModel nature.com/articles/s41467-0… @NatureComms

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18 May 2021
MRLocus: un novedoso modelo estadístico para determinar cómo la perturbación de la expresión génica o los elementos reguladores individuales afectarÔn a rasgos futuros. #NewResearch #GeneExpression #GWAS #eQTL #RPackage #BayesianModel (1/7)
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