Stathis Gennatas
@metadsr_
Followers
315
Following
881
Media
13
Statuses
176
ML for Precision Medicine, Neuroscience, @UCSF_Epibiostat, @UCSF_BCHSI, @UCSF_Ci2, @UCSF. https://t.co/JW4vkTnCUc #rstats #julialang
San Francisco, CA
Joined May 2009
Out now! Quantitative dissection of #conscious #awareness changes induced by #psychedelics, big5personality-style. https://t.co/NDyAU09dDm conducted at @Mila_Quebec+@mcgillu+@sunydownstate + @broadinstitute
@RCarhartHarris @michaelpollan @anilkseth @SamHarrisOrg @StanDehaene
6
66
202
Gradient boosting is on average the best algorithm for tabular data while CNN is the best for images. What to do when we have multimodal datasets? After 3 years of hard work Representational Gradient Boosting has been published at TPAMI
2
3
24
The Conditional Super Learner is out! @metadsr_ @interian and @mark_vdlaan . Why is cross validation limited to selecting one model (from a library ) independent of the covariates? Consequences of selecting a model conditional on the covariates… https://t.co/YWwOaWgSR4
0
1
2
Joint PhD Program in Computational Precision Health @UCSF + @UCBerkeley
0
1
5
We are the new twitter account for the ASA Statistics in Imaging Section. We tweet news about conferences, opportunities in imaging research, new imaging related articles, and other fun stuff! Please give us a follow and retweet. @AmstatNews @ENAR_ibs #JSM2021
1
26
46
New preprint, led by @oualid_benkarim, examining out-of-distribution prediction in #ABIDE + #HBN: Analytical tools are needed to get a handle on #untracked #diversity in multi-site cohorts https://t.co/17sVduBFeo
0
17
34
Our book is out! (Check out Chapter 1 for a ~decent intro to the field)
Congrats to editor Lei Xing & @StanfordAIMI contributors @curtlanglotz @james_y_zou @jonc101x @KristenYeom @liaojoe1 @OkyazEminaga on publishing a new book “Artificial Intelligence in Medicine: Technical Basis and Clinical Applications” https://t.co/aZU0TT8N6h
2
0
3
a big yes
Want an idiomatically Julia version of fastai2? Then join the FastAI.jl project! https://t.co/ZFp3gPB28G
0
0
0
I 💕 #JuliaLang ! It looks & feels like Python, with the speed of C++, the parallelism of Go, batteries included (especially for #DataScience), metaprog like Lisp, great libraries and a welcoming community. I wrote a Julia tutorial for Python programmers: come & join the party!
A really in-depth #JuliaLang for Pythonistas Colab notebook by @aureliengeron. The notebook will install the Julia environment and @GoogleColab provides free GPUs! https://t.co/VNQs4MWJ6l
24
187
864
Print it out, retweet, send the link to this nice piece by Nina Bai @ucsf to your friends...... Still Confused About Masks? Here’s the Science Behind How Face Masks Prevent Coronavirus
4
61
84
We've introduced a new #datascience track as part of our MAS in Clinical & Epidemiological Research degree program. Attend the upcoming info session May 6, 2020 to learn more: https://t.co/3w0ZooWEvZ
#epitwitter #realdealepi #academictwitter #biostatistics #publichealth
1
5
10
Community participation is a cornerstone of #PrecisionMedicine. @UCSF's #COVID19 #CitizenScience project will provide a wealth of real-time data to inform and help trace infection and spread. Sign up here https://t.co/xVs3gQR4y3 or by texting “COVID” to 41411 @gregorymmarcus
0
9
11
COVID (@ucsf) Chronicles, Day 3 Brief post today since–if you have time–spend it watching @YouTube video of me & 9 top @ucsf experts on #COVID19 epidemiol, virology, pathophys, clinical, treatment; & response @UCSFHospitals. 100 min very well spent https://t.co/EyCppS4Kzi (1/4)
6
77
128
Traits of #daily #social #exchange are linked to brain anatomy, with sex-dependent idiosyncrasies, led by @hannahmaykiesow
https://t.co/WLU4YdDYO7 Great collabo w/ @twiecki @leoschilbach @amarquand + @TheNeuro_MNI @McGillBME @MILAMontreal
5
29
71
Accepted at @NeuroImage_EiC: Deep-dive into #CCA for high-dimensional data, led by @HaoTingW713. https://t.co/AzJuDMh38Y Fantastic collabo w/ @DaniSBassett @sattertt @the_mindwanders @MouraoMiranda
@MILAMontreal @McGillBME @TheNeuro_MNI
2
40
100
Who do you trust? Man + Machine synergy for trustworthy and robust predictive modeling in Medicine and beyond. #ExpertAugmentedMachineLearning #AI #ML #MachineLearning #ComputationalMedicine
The #AI in medicine body of research is replete w/ doctors vs machines, largely ignoring their synergy. Now a paper from @GilmerValdes @metadsr_ @UCSF and collaborators nicely demonstrates EAML @PNASNews
https://t.co/MMaTBp6hmP
0
6
12
Imagine combining – on a single computational platform – all findings about normal and aberrant biological processes, from human populations, to individuals, to experimental organisms, to cells and molecules. That’s #PrecisionMedicine Read the story: https://t.co/aVROnhIg6U
2
16
40
Decision Trees are wonderfully intuitive but usually must be ensembled for accuracy. Or do they? Part 1 of our work on improving tree accuracy: The Additive Tree - with @GilmerValdes and team #ml #datascience #rstats
3
2
10