We make the world's largest collection of a deep-phenotype multi-omics datasets accessible to improve human health.
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Pheno.AI retweeted
Podcast about our Human Phenotype Project humanphenotypeproject.org/ describing our large-scale cohort, the clinical and genomic data collected, the goals, and the AI tools we're developing to model future health trajectories of people
Listen here: tinyurl.com/hme5bsz8
What's even more amazing, is that the podcast was generated in minutes using Google's new Notebook ML tool @JeffDean based only on a written pdf of our project. The podcast is coherent, fluent, and interesting. Mind blowing
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Pheno.AI retweeted
Our new @NatureAging paper: We built 14 "biological clocks" representing the biological age and rate of aging of 14 major body systems using data from 13,000 people of the Human Phenotype Project
Key findings:
1. Biological clocks are clinically meaningful: People with higher biological age for some body system are at greater risk for disease related to that body system (e.g., higher aging rate of insulin resistance associates with higher risk for diabetes)
2. Surprisingly, biological clocks for different body systems are mostly independent, i.e., a person with a higher rate of aging for one body system does not necessarily have higher aging rates in other body systems
3. Males and females age differently: While males age linearly, females exhibit a sharp non-linear increase between the ages 50-55. This sharp increase is associated with menopause. When comparing pre- and post-menopausal females of the same chronological age, we find that post-menopausal females have higher biological age for several body systems
Paper: tinyurl.com/5esb3f5h
Data: humanphenotypeproject.org
Access our aging models: tinyurl.com/42yctten
Great job by @Lee_Reicher1, @NoamBar7, @nastya_godneva, Yotam Reisner, @ZahaviLiron, Nir Shahaf, @AdinaBlueBird, in collaboration with Raja Dhir
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Pheno.AI retweeted
A new report on biological aging from the Human Phenotype Project with key insights on age-related diseases and gender-specific effects @NatureAging @WeizmannScience
Our new @NatureAging paper: We built 14 "biological clocks" representing the biological age and rate of aging of 14 major body systems using data from 13,000 people of the Human Phenotype Project
Key findings:
1. Biological clocks are clinically meaningful: People with higher biological age for some body system are at greater risk for disease related to that body system (e.g., higher aging rate of insulin resistance associates with higher risk for diabetes)
2. Surprisingly, biological clocks for different body systems are mostly independent, i.e., a person with a higher rate of aging for one body system does not necessarily have higher aging rates in other body systems
3. Males and females age differently: While males age linearly, females exhibit a sharp non-linear increase between the ages 50-55. This sharp increase is associated with menopause. When comparing pre- and post-menopausal females of the same chronological age, we find that post-menopausal females have higher biological age for several body systems
Paper: tinyurl.com/5esb3f5h
Data: humanphenotypeproject.org
Access our aging models: tinyurl.com/42yctten
Great job by @Lee_Reicher1, @NoamBar7, @nastya_godneva, Yotam Reisner, @ZahaviLiron, Nir Shahaf, @AdinaBlueBird, in collaboration with Raja Dhir
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Pheno.AI retweeted
“Biological clocks are clinically meaningful” @segal_eran
Our new @NatureAging paper: We built 14 "biological clocks" representing the biological age and rate of aging of 14 major body systems using data from 13,000 people of the Human Phenotype Project
Key findings:
1. Biological clocks are clinically meaningful: People with higher biological age for some body system are at greater risk for disease related to that body system (e.g., higher aging rate of insulin resistance associates with higher risk for diabetes)
2. Surprisingly, biological clocks for different body systems are mostly independent, i.e., a person with a higher rate of aging for one body system does not necessarily have higher aging rates in other body systems
3. Males and females age differently: While males age linearly, females exhibit a sharp non-linear increase between the ages 50-55. This sharp increase is associated with menopause. When comparing pre- and post-menopausal females of the same chronological age, we find that post-menopausal females have higher biological age for several body systems
Paper: tinyurl.com/5esb3f5h
Data: humanphenotypeproject.org
Access our aging models: tinyurl.com/42yctten
Great job by @Lee_Reicher1, @NoamBar7, @nastya_godneva, Yotam Reisner, @ZahaviLiron, Nir Shahaf, @AdinaBlueBird, in collaboration with Raja Dhir
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Pheno.AI retweeted
An impressive sleep study goes deep on links to lifestyle and diseases
—impact of gut microbiome and diet re: sleep apnea
—big contribution of lifestyle factors
—ability to predict across 16 body systems from sleep data
@NatureMedicine @segal_eran @WeizmannScience
nature.com/articles/s41591-0…
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The GluFormer model is one of @NVIDIA 's greatest advancements in #generativeAI in 2024.
We're just getting started—stay tuned for what's next. The future of AI is ours to shape!
👀 Deep dive into #NVIDIAResearch's greatest advancements in #generativeAI in 2024.
🎉 blogs.nvidia.com/blog/ai-res… ✨
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Pheno.AI retweeted
👀 Deep dive into #NVIDIAResearch's greatest advancements in #generativeAI in 2024.
🎉 blogs.nvidia.com/blog/ai-res… ✨
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