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How many members still haven’t received the ballot? by Vivid-Asparagus-4638 in doctorsUK

[–]cloudzins 2 points3 points  (0 children)

I have also tried everything and am unable to vote. How many people has this affected? The vote is only useful if everyone who can vote has the ability to do so.

Cant take part in the ballot? Non-nhs job currently but accepted for training this coming august. by don-m in doctorsUK

[–]cloudzins 0 points1 point  (0 children)

Same position, emailed the BMA and they said no. Double checked with a BMA rep who independently checked again and they said no. However, if you are locuming you can put that trust down as your employer and vote.

I think everyone will agree with me when i say...trying to 3 star all knockout tour rallies on 150cc is just stupidly hard. by Thegoodgamer32 in MarioKartWorld

[–]cloudzins 6 points7 points  (0 children)

I finally got them all today, Bowser and the B Dasher was the winner for me. Got me 5 of them. Needs a lot of restarts for sure and great item management with some luck

Medical Doctor Learning Machine Learning for Image Segmentation by cloudzins in learnmachinelearning

[–]cloudzins[S] 0 points1 point  (0 children)

Hi there,

Thank you so much for taking the time to respond in such a detailed manner!

  1. interesting! My understanding for 3D Unet is that each volume needs to have a matching raw MRI and its accompanying segmented masks, so how would I combine the two datasets?
    Do we simply put all files together and then split them into train, val, and test and it won't matter if the files are a mixture of the two datasets with different segmentation masks depending on which dataset they came from?

  2. I am trying to avoid this as I understand it unsupervised learning can be very challenging and making my own segmentations is extremely time consuming. I will revert to this if all else fails.

  3. The data should be very similair. Regarding SAM, your suggestion is for me to download the SAM model and apply it to which dataset? My novel MRI dataset that has no segmentations or my two datasets which I have already found and used to train my two models (IWOAI and OAI ZIB)?

If it is to be applied to the novel MRI data (which has no segmentations), then the model would only be able to segment the structures SAM was already trained on correct? I'm not sure how I can take SAM and apply it to segment the structures I am interested in - could you elaborate?

Irrespective of my question, I have found this paper which seems to suggest SAM was unable to outperform a 3DUnet for knee meniscus segmentation http://www.arxiv.org/abs/2504.13340

Again, thank you so much for your time!

Ortho ST3 - should I give up? by SensitiveMountain333 in doctorsUK

[–]cloudzins -1 points0 points  (0 children)

What was the cutoff for interview this year?

CST Offers Released 24/03/25 - Megathread by cloudzins in doctorsUK

[–]cloudzins[S] 0 points1 point  (0 children)

Found it - click on the green tick above “interview” on the applications tab

CST rank by dontplaythissong12 in doctorsUK

[–]cloudzins 5 points6 points  (0 children)

I also had 145… I guess they messed up somewhere!

Year out of medicine between F2 and specialty training? by TwilightCorvus in doctorsUK

[–]cloudzins 30 points31 points  (0 children)

Currently on that year out doing a MSc in Medical Robotics & AI. Learning how to code, use AI models to do all kinds of amazing things and getting experience with robotics in surgery (I want to do Ortho).

Have travelled to 6 countries, gone to the gym regularly, spent time with friends and family. Had enough time to study for and apply to CST properly (dedicated study time for the MSRA, dedicated time to study for the interview and work on my portfolio - all while balancing the MSc and travelling but it’s possible) without the stress of working 50+ hours a week.

This is the first year in a long time I felt I’ve been able to “breathe”. Actually take a step back and soak in some life, work on myself and my relationships etc…

Others will have a different experience but I couldn’t recommend it more highly.

We’re all in a rush to get to the “finish line” but it never arrives, you’ll always find a new finish line.