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naimavahab.bsky.social

@naimavahab.bsky.social
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COMBINE @combine1.bsky.social · 10/08/2026
📢 COMBINE Symposium 2026 Join students and early-career researchers at COMBINE Symposium 2026, part of ABACBS Conference 2026. 📅 16 Nov 2026 📍 RMIT University, Melbourne Early-bird registrations are open. Abstract submissions and travel awards are available. @abacbs.bsky.social
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 23/02/2026
The article by Sam Mainwood and Aashish Bhandari is now published. dl.acm.org/doi/10.1145/...
dl.acm.org
Semantic Encoding in Medical LLMs for Vocabulary Standardisation | Proceedings of the 2025 18th Health Informatics Knowledge Management Conference
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 30/01/2026
A book chapter from the lab: This chapter explores multi-omics integrative studies enabled by machine learning, presenting an overview of state-of-the-art methodologies and the foundational background. Suitable for both beginners & advanced bioinformaticians www.sciencedirect.com/science/chap...
sciencedirect.com
Multi‐omics applications in health and diseases
Multi-omics research has transformed our ability to study biological systems by capturing information across multiple molecular layers, including geno…
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Aashish Bhandari @aashishbhandari.com · 21/01/2026
Delighted to share the publication of our paper "𝘈 𝘤𝘰𝘮𝘱𝘢𝘳𝘢𝘵𝘪𝘷𝘦 𝘦𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘩𝘢𝘯𝘥𝘭𝘪𝘯𝘨 𝘮𝘪𝘴𝘴𝘪𝘯𝘨 𝘥𝘢𝘵𝘢 𝘱𝘰𝘪𝘯𝘵𝘴 𝘢𝘯𝘥 𝘮𝘰𝘥𝘢𝘭𝘪𝘵𝘪𝘦𝘴 𝘪𝘯 𝘦𝘭𝘦𝘤𝘵𝘳𝘰𝘯𝘪𝘤 𝘩𝘦𝘢𝘭𝘵𝘩 𝘳𝘦𝘤𝘰𝘳𝘥𝘴" in the 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗼𝗳 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀! www.sciencedirect.com/science/arti...
sciencedirect.com
A comparative evaluation of handling missing data points and modalities in electronic health records
Background: Healthcare data, generally available as electronic health records (EHR), provide rich insight for predictive modelling. A common challenge…
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 22/01/2026
Congratulations @aashishbhandari.com 👏
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025
Our latest paper presents EHR-QC 2.0, a major upgrade to our open-source pipeline for preparing and standardising biomedical & genomic EHR data for machine learning. 🔍 What’s new: LLM-enabled clinical vocabulary mapping Support for FHIR A web-based interface 🔗 papers.ssrn.com/sol3/papers....
papers.ssrn.com
<span>An accessible pipeline for LLM-driven medical concept mapping, automated OMOP and FHIR conversion</span>
Background:Our previous work introduced the open-source EHR-QC pipeline. This pipeline implements extraction, transform and load (ETL), pre-processing and quali
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025
Our latest review explores how RNA foundation models are reshaping predictions of ncRNA structure & function. We highlight key architectures, training strategies, and open challenges to guide the next phase of RNA-AI research. Read here 👉 link.springer.com/article/10.1...
link.springer.com
Advancing non-coding RNA annotation with RNA sequence foundation models: structure and function perspectives - BMC Artificial Intelligence
Noncoding RNAs (ncRNAs) form the major part of the expressed transcriptome. These are critical in regulating gene expression and contributing to disease mechanisms, primarily through their complex sec...
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025
Our latest paper combines multi-omics integration with genome-scale NLP models trained on DNA to uncover how S. aureus regulates infection, metabolism, and antibiotic resistance. This unique organism agnostic method offers a new lens for systems-level biology. 🔗 www.nature.com/articles/s41...
nature.com
Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models - Scientific Reports
Scientific Reports - Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models
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Sonika Tyagi @tsonika.bsky.social · 14/10/2025
New publication from the lab
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Sonika Tyagi @tsonika.bsky.social · 14/10/2025
Our invited editorial in BMC Artificial Intelligence along with @naimavahab.bsky.social
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Sonika Tyagi @tsonika.bsky.social · 31/01/2025
#hotoffthepress #newpublication from the #TyagiLab "EHR-ML: A Data-Driven Framework for Designing Machine Learning Applications with Electronic Health Records “ Pre-proof is online now: lnkd.in/gHHrFEGF
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 18/03/2025
Good work by @aashishbhandari.com #digitalhealth #missingdata #machinelearning #predictivemodeling #AIforHealth
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Sonika Tyagi @tsonika.bsky.social · 12/05/2025
New publication from the lab @tyagilab.bsky.social Applications of linguistics in genome language modeling academic.oup.com/biomethods/a...
academic.oup.com
Genome language modeling (GLM): a beginner’s cheat sheet
Abstract. Integrating genomics with diverse data modalities has the potential to revolutionize personalized medicine. However, this integration poses signi
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Sonika Tyagi @tsonika.bsky.social · 04/05/2025
New publication from the lab @tyagilab.bsky.social academic.oup.com/biomethods/a... #multimidaldata #biomedicaldata #dataharmonisation #tyagilab
academic.oup.com
Navigating the Multiverse: a Hitchhiker’s guide to selecting harmonization methods for multimodal biomedical data
Abstract. The application of machine learning (ML) techniques in predictive modelling has greatly advanced our comprehension of biological systems. There i
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Sonika Tyagi @tsonika.bsky.social · 18/06/2025
New preprint from the lab @tyagilab.bsky.social
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 12/07/2025
#Interpretable vs #explainable #AI 📖 An informative post by lab members @esha4.bsky.social and @tnavya.bsky.social 📖
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AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 22/07/2025
#foundationsofAI #AI #teaching
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Sonika Tyagi @tsonika.bsky.social · 24/09/2025
Congratulations to @yashpalr.bsky.social on his graduation! @tyagilab.bsky.social
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Aashish Bhandari @aashishbhandari.com · 25/09/2025
🩺 Missing medical data isn't just something to fill in or ignore! EHRs often have missing values. Common fix? Imputation. But filling gaps can mislead predictions. We explore ML approaches to handle missingness while preserving the original data distribution. 📜 www.researchsquare.com/article/rs-6...
researchsquare.com
Mind the Gaps: Guess Less, Predict More with Missing Medical Data
Healthcare data, generally available as electronic health records (EHR), provide a rich profile of an individual’s health and lifestyle. This data can be harnessed for predictive modelling using machi...
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naimavahab.bsky.social @naimavahab.bsky.social · 25/09/2025
A versatile machine learning pipeline to find co-regulatory modules (CRMs) in DNA. Check it out and explore: doi.org/10.1016/j.co... #Genomics #Epigenomics #MachineLearning #CardiacResearch #OpenScience @tyagilab.bsky.social @tsonika.bsky.social
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