Single-Cell Raman Spectra for Predicting Acute Myeloid Leukemia Treatment Response

Raman spectroscopy data from bone marrow cells of newly diagnosed acute myeloid leukemia patients predicts chemotherapy resistance. The prediction model achieved 94.8% accuracy and a 96.27% AUC in external validation. Author Ming Zhang published this research dataset under a CC-BY-4.0 license in April 2026.

Use Cases

• Predicting patient chemotherapy response based on single-cell metabolic fingerprints.
• Analyzing metabolic reprogramming features associated with drug resistance in leukemia.
• Building prognostic stratification models using spectroscopic data and machine learning.

Strengths

• Model performance metrics are provided, including 94.8% accuracy and a 96.27% AUC.
• The dataset is described as enabling marker-free, highly sensitive prognostic stratification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 12.5 MB DOCX, which may not be a standard data format for direct analysis.

Provenance

Source

figshare

Collection Method

Bone marrow single cell Raman spectroscopy data were collected from patients and analyzed with PCA-LDA and MCR-ALS methods.

Freshness

Last updated 2026-04-28 05:27:53; freshness should be verified.