Full-stack clinician and engineer | improving front-end patient care through back-end biomedicine, data science, and tech

Cambridge, UK
Joined November 2018
Over the coming weeks, we will be introducing Prima Mente to the world. We kicked off today at @NVIDIAGTC Paris highlighting two foundational collaborations: @nebiusai has become a core partner for our work to generate the world’s largest brain foundation models. Our goal long-term: understand the brain across health, age, and disease. Through @nvidia DGX Cloud with Lepton, we have started to scale our exciting work in Alzheimer’s Disease to Parkinson’s. Thank you to Arkady Volozh and Jensen Huang for supporting what will be the biggest application of AI in our world today - human health. It is a privilege to work with both the @nvidia (Janisha Anand, @cedricSteenb, Ben Griffiths) and @nebiusai (@romanchernin, Danila Shtan, Ilya Burkov, Hasan Göktuğ Çolak, Anastasia Ustinova) teams. Links to both press releases are in the thread.
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🚨 We’re #hiring a Staff Scientist to drive innovative computational workflows for large-scale, multi-omics data in human microbiome research @LawleyLab @sangerinstitute 📅 Closing date: 27th April 2025 📢 Please share & apply! sanger.wd103.myworkdayjobs.c…
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How should we evaluate #LLMs for downstream clinical use cases? In this @npjDigitalMed article, we propose a transition from static QA-style benchmarks to dynamic agent-based simulators, similar to methods used in biology, epidemiology & social sciences. nature.com/articles/s41746-0…
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Congratulations to my student @tenghiangh on her first PhD preprint! It's about recessive associations in @GenesHealth , a cohort of >40k British South Asians. See her thread for an account and the paper here medrxiv.org/content/10.1101/….
When we think of recessive conditions, rare monogenic disorders come to mind. Yet variants have recessive effects on common diseases too! We profiled the single-variant recessive landscape of a cohort of 44k British South Asians, now live on medRxiv: (1/11)
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Our paper describing a way to infer the phase of rare variant pairs using gnomAD v2 is out now in Nature Genetics. We hope that the resource we generated will be useful when interpreting rare co-occurring variants in the context of recessive disease. nature.com/articles/s41588-0…
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So brilliant that @DrXiaoLiu @sktywagner could showcase for @RishiSunak our work on #oculomics #FoundationModels #RETFound and #Equity #Safety of AI-enabled Healthcare Proud UK can be a leader in Artificial Medical Intelligence 🇬🇧🇬🇧 @Moorfields @UCLeye @uhbtrust @unibirmingham
Replying to @RishiSunak
@RishiSunak was @Moorfields this morning, for a live demo from @sktywagner and @DrXiaoLiu of how INSIGHT is enabling world-leading research using AI to detect disease from retinal scans. @UCLeye @uhbtrust msn.com/en-gb/travel/news/ri…
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MTF is excited to announce we will be delivering a talk as part of Ipswich Hospital's Basic and Laproscopic Surgical Skills Course. The event is free to attend and will be in person at Ipswich Hospital on October 13th. Hope to see you there!
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Is anyone here using the UKBiobank 200k genomes dataset? We are having some weird issues and are trying to troubleshoot if data vs code 😬 Anyone else seeing anything odd? Either way, please share! 🧬
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Great lineup for the inaugural webinar from the Consortium for Vision and Oculomics in Psychiatry @CVOPorg
🌟Exciting news! 🧠👁 Join CVOP's inaugural webinar, "From Eye to Brain: Oculomics and Schizophrenia"! 🚀 Register now at cvop.org/fromeyetobrain to dive into the fascinating world where #Psychiatry and #VisionScience intersect. #AcademicTwitter #ScienceCommunity
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Congratulations @sktywagner! 🥳🤩Speaking for the whole group when I say we are incredibly proud of the many feats you’ve achieved this year and excited for the way your work and #AlzEye will propel #oculomics ! A #risingstar indeed @OphthoMag 👏🏽
👏Congratulations to @sktywagner - one of ten rising stars on @OphthoMag's 2023 Power List. Siegfried is a core member of the research group supported by INSIGHT in advancing the field of #oculomics @Moorfields @UCLeye @MoorfieldsBRC 🔗Read more: bit.ly/45jYLQL
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Very pleased our manuscript is out today at @CellCellPress on the influence of autozygosity on common disease risk: doi.org/10.1016/j.cell.2023.… Thank you to the thoughtful reviewers that helped us improve our work! Check out the thread below for a summary of the main results
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Great paper by @DMalawsky, @hilsomartin and the team on the associations of consanguineous union with common diseases. Consanguinity (i.e., marrying close relatives e.g. cousin marriages) results in the passing of very similar genomes from father and mother to the offspring. This increases the load of recessive deleterious mutations in the offspring, which can be inferred from genetic data by quantifying the stretches of homozygous genotypes (described as autozygosity). Consanguineous marriages are highly common in many South-Asian populations. The negative health consequences of consanguineous unions are well known in the context of rare recessive severe diseases such as skeletal deformities, intellectual disability etc. However, the effect of consanguineous unions on the risk of common diseases is not well studied. This is very important as diseases like type-2 diabetes are highly common in South-Asian populations. Here by analyzing genetic and phenotypic data of two South-Asian cohorts, the authors show that consanguinity strongly increases the risks of even common diseases. For example, in communities practising consanguineous marriages, more than 10% of type 2 diabetes might be due to autozygosity (and this is probably an underestimate). What type of genetic variants are mediating the association between autozygosity and increased risk of common diseases? Likely rare recessive variants acting in a non-additive manner. To pinpoint which recessive variants are driving which diseases, we will need extremely large sample sizes as homozygous genotypes are extremely rare (square of minor allele frequency). An important research contribution to the South-Asian communities by Malawsky et al. 👏👏
Very pleased our manuscript is out today at @CellCellPress on the influence of autozygosity on common disease risk: doi.org/10.1016/j.cell.2023.… Thank you to the thoughtful reviewers that helped us improve our work! Check out the thread below for a summary of the main results
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Feeling very proud to have worked with Yukun, Pearse, and the team on research like this over the past couple of years. The potential is enormous - @ucl @cdt_ai_health & @Moorfields is THE place to be for creating responsible, impactful AI with a focus on future patient benefit.
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> half the time a masked reading center disagreed with treatment decisions in ROP. @irop_consortium working on AI solution to standardize diagnosis with siloamvision.com ophthalmologyretina.org/arti…
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New preprint from the team 🎉 Thread from incredible postdoc @Alextremophile who led this work below 👇 Thank you to all the team, collaborators, clinicians, and of course the @GenomicsEngland participants for making this happen. As always, feedback very welcome!
I am breaking a long twitter hiatus with some exciting news: 🚨A new preprint!🚨 medrxiv.org/content/10.1101/… I am super excited to be sharing this, and hope you enjoy reading it! Key points (A 🧵):
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Just published @Nature 1st major large language model in medicine Self-supervised #AI of 2 million retina images to predict many diseases beyond the eye, such as heart attack, stroke, heart failure, Parkinson's disease nature.com/articles/s41586-0… led by @pearsekeane @Yukunzhou19
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Privileged to work with all team members for RETFound, and thanks for great mentorship from all senior researchers. Looking forward to more exciting work down the road!🥂
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We are thrilled to share that our new retinal foundation model, "RETFound" published today in @Nature! To our knowledge, RETFound is the first #opensource foundation model for retinal images and one of the earliest across all medical imaging fields. nature.com/articles/s41586-0…
Just published @Nature 1st major large language model in medicine Self-supervised #AI of 2 million retina images to predict many diseases beyond the eye, such as heart attack, stroke, heart failure, Parkinson's disease nature.com/articles/s41586-0… led by @pearsekeane @Yukunzhou19
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