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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
Tomer Meir, PhD: AI for healthcare, causal inference, survival analysis, and hybrid mechanistic models for personalized medicine.
Research background
Tomer Meir’s education, healthcare research, and machine learning teaching at the Technion, Weizmann Institute, and Zebra Medical Vision.
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Publications
Publications by Tomer Meir on causal inference, survival analysis, hybrid models, and medical imaging, including ICML, Biometrics, and JOSS.
Posts
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Blog Post number 4
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Blog Post number 1
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conferences
Conferences
2022 - Machine Learning in Healthcare (MLHC) - PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks 2021 - 15th NATO Operations Research \& Analysis - COVID 19 data analysis and modeling - keynote
2021 - NATO webinar - Israel’s Best Practices in Enhancing Resilience – the Case of Covid-19
2020 - ICML HSYS (Spotlight) - Who should we test for COVID-19? A triage model from national symptom surveys
2020 - ICML HSYS - Rapid deployment of a nationwide symptoms survey - framework and applications
2020 - MICCAI - 3D convolutional sequence to sequence model for VCF identification in CT
2019 - X International Conference of the Georgian Mathematical Union - Buckling of columns with non-ideal boundary conditions
portfolio
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projects-covid
Data-driven COVID-19 response
Survival modeling, symptom surveillance, and population-level evidence for public-health decisions.
projects-hte-tte
Personalized treatment effects with censored outcomes
MISTR: estimating heterogeneous treatment effects when survival outcomes are incompletely observed.
projects-hybrid
Hybrid mechanistic–data-driven models for personalized time-dependent intervention outcomes
Combining mechanistic knowledge and neural networks for robust prediction under time-dependent interventions.
projects-pydts
Discrete-time survival analysis with competing events and PyDTS
Efficient discrete-time competing-risks regression and an open-source Python toolkit.
projects-vcf
Detecting vertebral fractures in CT
A compact spine representation and 3D sequence model for vertebral compression fracture detection.
publications
talks
Talks
2021 - 15th NATO Operations Research \& Analysis - COVID 19 data analysis and modeling - keynote 2021 - NATO webinar - Israel’s Best Practices in Enhancing Resilience – the Case of Covid-19 2020 - ICML HSYS (Spotlight) - Who should we test for COVID-19? A triage model from national symptom surveys 2020 - ICML HSYS - Rapid deployment of a nationwide symptoms survey - framework and applications 2020 - MICCAI - 3D convolutional sequence to sequence model for VCF identification in CT 2019 - X International Conference of the Georgian Mathematical Union - Buckling of columns with non-ideal boundary conditions
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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