Pith Number

pith:2YU3I47I

pith:2026:2YU3I47IXVNMDLW6XV2627XJOL

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Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning

Ardhendu Behera, Saqib Nazir

A deep learning model jointly classifies white blood cell types and regresses protein expression levels from label-free DPC images.

arxiv:2605.14717 v1 · 2026-05-14 · cs.CV · cs.AI

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\pithnumber{2YU3I47IXVNMDLW6XV2627XJOL}

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4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We present a unified Deep Learning (DL) framework that jointly performs White Blood Cell (WBC) classification and continuous protein-expression regression from label-free Differential Phase Contrast (DPC) images.

C2weakest assumption

The assumption that bright-field morphology in DPC images contains enough information to accurately infer molecular phenotypes such as protein expression levels.

C3one line summary

A hybrid CNN-transformer model with multi-task learning achieves 91.3% WBC classification accuracy and 0.72 Pearson correlation for CD16 expression regression from label-free DPC images, augmented by LLM-generated summaries.

References

28 extracted · 28 resolved · 2 Pith anchors

[1] TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation 2021 · arXiv:2102.04306

[2] Lab on a Chip24(5), 924–932 (2024) 2024

[3] arXiv: Learning (2016),https: //api.semanticscholar.org/CorpusID:125617073 2016

[4] In: International Conference on Learning Representations (2021) 2021

[5] Google DeepMind: Gemini 2.5 pro model card.https://deepmind.google/(2024) Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning 15 2024

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:38:59.154264Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d629b473e8bd5ac1aedebd75ed7ee972fe1c05d1f3235610fddb0ae1093c5817

Aliases

arxiv: 2605.14717 · arxiv_version: 2605.14717v1 · doi: 10.48550/arxiv.2605.14717 · pith_short_12: 2YU3I47IXVNM · pith_short_16: 2YU3I47IXVNMDLW6 · pith_short_8: 2YU3I47I

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2YU3I47IXVNMDLW6XV2627XJOL \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d629b473e8bd5ac1aedebd75ed7ee972fe1c05d1f3235610fddb0ae1093c5817

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "47418b03062ea212601907e35856585c58266b419f2633dcd61a24c032a356c7",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-14T11:38:56Z",
    "title_canon_sha256": "8b7acd303cb51698049ded15074f9e9ce127e44b5ec1a1873d85adcd942f3d82"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14717",
    "kind": "arxiv",
    "version": 1
  }
}