Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.
Timothy B FisherGeetanjali SainiT S RekhaJayashree KrishnamurthyShristi BhattaraiGrace CallagyMark WebberEmiel A M JanssenJun KongRitu AnejaPublished in: Breast cancer research : BCR (2024)
Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.
Keyphrases
- machine learning
- neoadjuvant chemotherapy
- end stage renal disease
- transcription factor
- locally advanced
- chronic kidney disease
- ejection fraction
- newly diagnosed
- artificial intelligence
- lymph node
- sentinel lymph node
- big data
- case report
- peritoneal dialysis
- squamous cell carcinoma
- early stage
- radiation therapy
- patient reported outcomes
- combination therapy