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How to handle class imbalance in a medical image classification dataset? (51)

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Growing 70 pts 0 followers
PES University · Posted
Astronomy & Astrophysics Cybersecurity

Problem statement

I am working on a bioinformatics project analyzing GWAS data for a rare Indian genetic disorder. My sample size is only n=89 cases and n=143 controls due to the rarity of the condition.

Specific questions:

  1. Should I report power analysis even though I know the study is underpowered?
  2. Bonferroni seems too conservative with this sample size; is FDR acceptable?
  3. I don't have an independent cohort to validate. Is this a dealbreaker for journal submission?

This is a legitimate clinical study with IRB approval. I just want to know how to frame the limitations honestly.

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9 Replies

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Sowmya Narayanan Active 310 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Jagdish Rawat · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

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Replying to Jagdish Rawat
Ganesh Menon Growing 140 pts · Accepted answer

Check whether your institution has a Springer/Elsevier waiver agreement.many NITs and IITs do.

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Replying to Jagdish Rawat
Deepa Krishnamurthy Distinguished 810 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Replying to Jagdish Rawat
Farhan Mirza · Accepted answer

Open access is the right direction but the APCs are prohibitively expensive for many Indian researchers without institutional funding.

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Admin NITK · Accepted answer

Great question.I went through something very similar in my second year.

The key insight for me was that LoRA is actually quite well-suited for NER tasks, especially in low-resource settings. I would recommend:

  1. Use LoRA with r=8 or r=16.don't go higher for 8K samples
  2. Apply LoRA to attention layers only, not the feed-forward layers
  3. Use a cosine learning rate schedule with warm-up (10% of steps)

For Telugu-English code-mixed NER specifically, you might also look at MuRIL.it is pretrained on Indian language data and often outperforms XLM-R on Indic tasks even with less fine-tuning data.

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Rohan Desai Distinguished 950 pts · Accepted answer

Overleaf + GitHub integration is underrated. You get version control and collaboration in one place.

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Replying to Rohan Desai
Aditya Sharma Starting 45 pts · Accepted answer

Just to make sure I understand the Zotero workflow correctly.is the .bib file synced to Overleaf automatically every time you add a new paper, or do you need to trigger an export manually?

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Zara Hussain Growing 55 pts · Accepted answer

I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.