Selma Yeni Yildirim

ORCID: 0000-0002-5925-561X
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About
Contact & Profiles
Research Areas
  • Cancer Cells and Metastasis
  • Cancer-related Molecular Pathways
  • Advanced Breast Cancer Therapies
  • Cancer-related cognitive impairment studies
  • AI in cancer detection
  • Endometrial and Cervical Cancer Treatments
  • Bioinformatics and Genomic Networks
  • Cancer Genomics and Diagnostics
  • Immune Cell Function and Interaction
  • Gene expression and cancer classification
  • Lung Cancer Treatments and Mutations
  • Cancer Immunotherapy and Biomarkers
  • Radiomics and Machine Learning in Medical Imaging

Memorial Sloan Kettering Cancer Center
2024

Hacettepe University
2022

Artificial intelligence (AI) systems can improve cancer diagnosis, yet their development often relies on subjective histologic features as ground truth for training. Herein, we developed an AI model applied to whole-slide images using CDH1 biallelic mutations, pathognomonic invasive lobular carcinoma (ILC) in breast neoplasms, truth. The accurately predicted mutations (accuracy = 0.95) and diagnosed ILC 0.96). A total of 74% samples classified by the having but lacking these alterations...

10.1158/0008-5472.can-24-1322 article EN Cancer Research 2024-08-06

Inhibition of CDK4/6 kinases has led to improved outcomes in breast cancer. Nevertheless, only a minority patients experience long-term disease control. Using large, clinically annotated cohort with metastatic hormone receptor-positive (HR+) cancer, we identify TP53 loss (27.6%) and MDM2 amplification (6.4%) be associated lack Human cancer models reveal that p53 does not alter activity or G1 blockade but instead promotes drug-insensitive p130 phosphorylation by CDK2. The persistence...

10.1016/j.ccell.2024.09.009 article EN cc-by-nc Cancer Cell 2024-10-10

<div>Abstract<p>Artificial intelligence (AI) systems can improve cancer diagnosis, yet their development often relies on subjective histologic features as ground truth for training. Herein, we developed an AI model applied to whole-slide images using <i>CDH1</i> biallelic mutations, pathognomonic invasive lobular carcinoma (ILC) in breast neoplasms, truth. The accurately predicted mutations (accuracy = 0.95) and diagnosed ILC 0.96). A total of 74% samples classified...

10.1158/0008-5472.c.7494045 preprint EN 2024-10-15
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