Machine Learning and Mental Health Lab

We use machine learning and digital technologies to better understand mental health disorders. Our main projects:

[Machine Learning and Mental Health Lab @mlmh_lab]

If you’re a psychologist, psychiatrist or neuroscientist looking to learn about machine learning applications to brain disorders check out our new book! Written by experts in the field and with a tutorial in Python to get you started! https://t.co/zyqQt9I11b

[Machine Learning and Mental Health Lab @mlmh_lab]

Our review and meta-analysis on machine learning for predicting who will benefit from CBT has been just published in Clinical Psychology Review! @sandra___vieira @raquelg_18

https://t.co/M8wUGJ8igk

[Sandra Vieira @sandra___vieira]

**New position** Our team is hiring a postdoc to work on a AI tool to detect brain-based disorders. If you're interested or have any questions please message me or the @mlmh_lab. Please share with anyone that may be interested! @KingsIoPPN @KingsJobs
https://t.co/pBZAN8weDi

[Machine Learning and Mental Health Lab @mlmh_lab]

The MLMH lab is hiring! We are looking for a postdoc interested in machine learning/deep learning applications to structural MRI in psychiatric and neurological disorders. Please rt.

https://t.co/6Ov378gsqC

[Machine Learning and Mental Health Lab @mlmh_lab]

If you're interested in machine learning and brain age check out our new paper led by Lea Baecker! It provides a state-of-the art review, introduces the main methods and discusses clinical applications @EBioMedicine @Don_Rafael @sandra___vieira @CScarpazza https://t.co/iJLwGZiaCe

[Machine Learning and Mental Health Lab @mlmh_lab]

Interested in brain age but not sure how to analyse your data? Our most recent paper in @OHBM tests different pipelines and provides recommendations! Check out the paper highlights by one of the study leads @Warvito (link to code included below!)

[Walter Hugo Lopez Pinaya 🍍 @Warvito]

Check out our new paper comparing different methods and preprocessing to predict brain age

w/ Lea Baecker @jessdafflon @pfdacosta Rafael Garcia-Dias @sandra___vieira Cristina Scarpazza @vdcalhoun João Sato Andrea Mechelli

@mlmh_lab

https://t.co/kc6YgT0CDX

[Machine Learning and Mental Health Lab @mlmh_lab]

Our very own @sandra___vieira has been awarded the prestigious and highly competitive Sir Henry Wellcome Postdoctoral Fellowship from the @wellcometrust to develop predictive models in early psychosis. Congradualtions Sandra!🥳@KingsIoPPN @PSYSCANproject

[Lilla Porffy @LillaPorffy]

I don't have a large twitter following, but some of you might be able to help spread the word of my experience getting the Pfizer Covid vaccine today.

[Sandra Vieira @sandra___vieira]

The @PSYSCANproject is hiring! The data manager will have a key role in the project. Excellent opportunity to work in one of the largest and most exciting projects in psychosis. Pls RT https://t.co/Gi2oYwm7ov

[Machine Learning and Mental Health Lab @mlmh_lab]

If you’re a psychologist, psychiatrist or neuroscientist looking to learn about machine learning applications to brain disorders check out our new book! Written by experts in the field and with a tutorial in Python to get you started! https://t.co/zyqQt9I11b

[Machine Learning and Mental Health Lab @mlmh_lab]

What a fantastic initiative form the @wellcometrust! First data challenge in mental health. We looking forward to knowing more about the challenge (and the prizes)!

[Prof Miranda Wolpert @mirandarwolpert]

https://t.co/vuvQ8EMlec

[Sandra Vieira @sandra___vieira]

Come and join us for 5-day winter school on modern statistical approaches to MRI data! Learn from world experts in lovely Padua and/or remotely (TBD) about MRI, fMRI, connectivty, machine learning and more! For more details see https://t.co/TVkiwRVXcQ Pls RT

[Machine Learning and Mental Health Lab @mlmh_lab]

You can check out Neuroharmony at https://t.co/KRhn5mw2kY

[Machine Learning and Mental Health Lab @mlmh_lab]

The final version of our new paper is now out @NeuroImage_EiC! Scanner Harmonization for unseen scanners. Well done @Don_Rafael!

https://t.co/8g9N8vCMHY

[Sarah Morgan @Sarah_Morgan_UK]

1 week left to apply!

[Francisco Pereira @fpereira]

The Machine Learning Team at NIMH is hiring a machine learning research scientist:

https://t.co/oU9kckEf0F

We help NIMH scientist use machine learning to solve research problems. We have amazing datasets, technical resources, and collaborators! Please RT or repost, thank you!

[Machine Learning and Mental Health Lab @mlmh_lab]

Several approaches have been developed to harmonise MRI data from different known scanners. But what about hamonising data from unknown and unseen scanners? Check-out our lab’s latest paper led by @Don_Rafael https://t.co/DXSMOSGSFK

[Sarah Morgan @Sarah_Morgan_UK]

Excited to advertise a 1 year Post-Doc position to develop markers of psychotic disorders from transcribed speech data. We'll be using Natural Language Processing & Network Science approaches. Please share/message me any qu.s! @turinginst @psychiatry_ucam https://t.co/8MgZIYqqO2

[Seyed Mostafa Kia @smkia83]

0/7 The preprint of our recent work on “Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data” is available at https://t.co/tTsup9Nfis. #MICCAI2020

@amarquand @HesterHuijsdens @dinga92 @ThomasWolfers @MaartenMennes @oleaandreassen @larswestlye

[Seyed Mostafa Kia @smkia83]

6/7 Using a large dataset of 7499 participants aggregated across 33 scanners, we experimentally demonstrate the superiority of HBR in estimating the predictive posterior distribution compared to trivial pooling and ComBat harmonization.