Nipun Nagpal’s Post

DATA LOOPS; DO WHILE (i LE 10); i+1; END; RUN; DATA LEEPS; DO UNTIL (i GE 10); i+1; END; RUN; WHAT WILL BE THE OUTPUT FOR LOOPS AND LEEPS DATASETS? #SAS_Challenge #ClinicalResearch #ClinicalTrials #DrugDevelopment

"Would you take the medicine yourself?" 💊 ✔❌ During the workshop Causal Reasoning, moderator Marnix Zoutenbier asked this question to the audience in three different situations. Although in 2 situations the dataset was exactly the same, the answer turned out to be completely different! This workshop was part of our internal #TechnologyDay, last week. Creating awareness amongst colleagues of how you can easily make wrong decisions with data. And how big a role context and existing (domain) knowledge play. #knowledgesharing #data #engineering

Over 50% of researchers find their data management tools inadequate or cumbersome. QuantiNova is here to simplify your process, offering seamless data management and analysis all in one place. Enjoy effortless integration with essential services and streamline your entire research workflow. We get it—juggling multiple tools can be exhausting. Let QuantiNova make it easier for you! #medicalresearch #StatisticalAnalysis #statistical #quantinova #research #researcher

When you're on holiday and nature reminds you of your work. #CellSegmentation is one of the biggest challenges in the analysis of #SpatialTranscriptomics data.

A quick reflection after a last week's meeting: The mere fact that we randomize the treatment does not guarantee that we can answer arbitrary causal questions. Well-designed randomization allows us to address interventional questions under the stable data generating process assumption. It's both little and a lot.

Join Alex Rutkovsky, Matteo Luberti, and Mike Lelivelt of Illumina for a panel discussion about the essential concepts and benefits of #SingleCell analysis and why you should consider it for your research. Register at https://lnkd.in/gPPM97Wc Topics: ·      What single cell data analysis is & how it differs from bulk analysis ·      Basic steps of the single cell analysis pipeline including cell typing ·      How to explore & interpret data visualizations

👋 Are you a clinical hashtag #microbiologist? If so, you might find this short video interesting! See how GIDEON supports you with real-case applications, pathogen identification, and cutting-edge data visualization tools. Watch here: https://bit.ly/3Vajvcn

Transform Maintenance with Real-Time Analysis 🧪✨ Combining lab analysis with real-time data empowers you to make well-informed decisions about your maintenance routines. Track the impact of specific actions on your equipment with the support of big data and rigorous lab science. Stay ahead with smarter maintenance strategies! #BigData #LabScience #EquipmentMaintenance

Loved our recent blog post about the built in model libraries in #MonolixSuite, https://lnkd.in/gHbQ_Wzh? Want to know more? 👉 Explore our #documentation here: https://lnkd.in/gnpcP-Jv It provides a complete overview of all library models, including equations, detailed descriptions, and step-by-step guidelines to help you select the best model for your data. #SimulationsPlus #modeling #pharmacometrics #PKPD

📚 Types of Cross-Validation: -K-Fold Cross-Validation -Stratified K-Fold Cross-Validation -Leave-One-Out Cross-Validation (LOOCV) -Leave-P-Out Cross-Validation -Time-Series Cross-Validation: Can you list any disadvantages of this cross-validation techniques? Add it in comment section 💬 #data #datascience #dataanalytics