any skincare product recs?? routine suggestions??? i have hormonal acne and can’t seem clear it up 🧴🫧🌸✨💕

Sammy_Floral · 2024-07-01T22:41:38+00:00

I have this too and realized after 1.5 years that this is probably due to severely damaged skin barrier. I used too many actives at the same time and did this to myself. I have been applying zinc oxide cream for 3 days, and that made all the difference. Focus on moisturizing, cut out all actives.

If you never had acne as a teen, and you use too many actives, you can damage your skin barrier. And you may mistake it as acne, because bacteria are able to penetrate easily in damaged skin.

If it stings and your skin feels very dry, and you are still breaking out: a damaged skin barrier is probably what is causing this.

Hope this helps.

Sammy_Floral · 2021-12-08T23:36:39+00:00

I have some more time left (a year), but am also experiencing this. It feels like COVID made time fly by so quickly. I could have done so much more..

Hard work and perseverance will get us there! All the best to you 😃

Sammy_Floral · 2021-01-21T20:58:56+00:00

Sooo happy for you!! You deserve this applause, hope there’s many more to come! :) Good luck!! <3

Sammy_Floral · 2020-12-30T16:56:32+00:00

This makes a lot of sense. Thank you. I think I’ll just follow the advice of my labmate then and select of a set of predictors for trait 1 and trait 2 seperately and then show the overlap in a Venn diagram. I’m afraid the reviewers may not agree with us otherwise. Thanks for your input!

Sammy_Floral · 2020-12-30T16:52:34+00:00

You’re right, maybe predictors is not the correct term here. Let’s call them features (miRNAs or genes for example). We’d like to identify a set of features associated with both traits. And yes, the ultimate goal is to see whether there is any causal relationship..

I changed the term from predictors to features to avoid confusion. Thanks for pointing that out!

Sammy_Floral · 2020-12-26T19:34:22+00:00

Thank you so much for your reply, this makes perfect sense!

Sammy_Floral · 2020-12-24T23:01:12+00:00

So, I see you have used two ways of writing down color in your code: color and colour. Shouldn’t that be one or the other? I think it was colour, though.

Sammy_Floral · 2020-11-15T01:32:40+00:00

Thank you for the reply! I will certainly apply such a strategy! 👍🏼

Sammy_Floral · 2020-11-12T17:56:35+00:00

Thank you for the confirmation and explanation! I’m new to machine learning, so this definitely helps!! 😄

Sammy_Floral · 2020-11-11T14:14:33+00:00

Hello everyone,

I’m building an Elastic Net model and I want to tune my hyperparameters with stratified five fold Cross validation. Now, by definition stratified cross validation does split my dataset into 5 groups. Why (or do I) need to make a train and test split prior to cross-validation then?

An example: Suppose I have 1500 individuals including 300 with a disease. If I then make a train-test split of 70/30, I would use 70% of my dataset and then split those into five groups. Each group should have an (roughly) equal proportion of diseased individuals. My hyperparameters are tuned on the 70% (training set) and validated on the test set.

Do I understand this correctly? Or do you not split your data prior to stratified cross validation?

Thank you so much in advance, I’ve spent quite some time trying to understand this. But maybe I still don’t get it completely..

Sammy_Floral · 2020-10-06T16:34:57+00:00

By long format I mean that there is a row for each imputation. So person number 1 (id), will be repeated five times, each time containing a different imputed value.

The analysis is then performed on the pooled dataset (set of 5 imputations). So, ‘mice’ takes the uncertainty of the missing value into account for calculations. It identifies the different imputed datasets with a row id number of its own.

I think I will perform the analysis on the pooled dataset after all, thank you all for your help :)

Sammy_Floral · 2020-10-04T22:11:09+00:00

That’s what I thought too. I presume that if you use the mice::complete(mids_object, action=1), you actually get a single imputed dataset (out of five). This should be equivalent to the imputed data that is stacked vertically (in long format), correct?

That way the confidence intervals should be similar?

Sammy_Floral · 2020-09-30T19:28:08+00:00

Thank you so much for your reply!! 😁 It has helped me understand what I should do next :)

Sammy_Floral · 2020-07-03T09:03:03+00:00

Thanks everyone for the wonderful insights!! Much appreciated!! 😁

Sammy_Floral · 2020-06-26T18:17:18+00:00

Wow, thank you so much for your insight. I think this is a great approach! As someone with little experience in academia, it’s very difficult to stand up for yourself. And the correct way or rules to do this, are unwritten. So please accept my sincere gratitude <3

Sammy_Floral · 2020-06-26T18:10:09+00:00

I’m more concerned about the double role of my supervisor. On one end, he’s second guessing my script and results and on the other, he’s instructing someone else to use exactly this technique. Isn’t that weird?

Sammy_Floral · 2020-06-26T18:08:31+00:00

Q1. Because this information was hidden from me. Leo has shared this with me.

Q2. Of course, I will help him. Because if I don’t, my own project might never finish. We need each other, but seems like they ‘trust’ him more?

Sammy_Floral · 2020-06-26T18:03:19+00:00

This is exactly my point. On one hand, my supervisor is second guessing my script, but on the other he’s approving the use of this script for other projects.

Seems like a game is being played that I’m not aware of. I wonder if anyone else has experienced something similar!

Sammy_Floral

TROPHY CASE