ArticleFundamental research2024
Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer.
Article in Fundamental research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Artificial intelligence for triple-negative breast cancer from imaging to multi-omics.Frontiers in oncology · 2026Review
- Clinical Outcomes and Treatment-Related Complications in Triple-Negative Breast Cancer: A Review of 24 Case Reports from 2020 to 2025.Therapeutics and clinical risk management · 2026Review
- Development and validation of an artificial intelligence system for triple-negative breast cancer identification and prognosis prediction: a multicentre retrospective study.EClinicalMedicine · 2025Article
- An Explainable Multimodal Artificial Intelligence Model Integrating Histopathological Microenvironment and EHR Phenotypes for Germline Genetic Testing in Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.Bioelectronic medicine · 2025Review
- Advances in Breast Cancer Care: The Role of Artificial Intelligence and Digital Pathology in Precision Medicine.European journal of breast health · 2025Article
- Artificial intelligence-based diagnosis of breast cancer by mammography microcalcification.Fundamental research · 2025Article
- Instance-level semantic segmentation of nuclei based on multimodal structure encoding.BMC bioinformatics · 2025Article
- The next frontier in antibody-drug conjugates: challenges and opportunities in cancer and autoimmune therapy.Cancer drug resistance (Alhambra, Calif.) · 2025Review
- ZNF689 deficiency promotes intratumor heterogeneity and immunotherapy resistance in triple-negative breast cancer.Cell research · 2024Article
- A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives.Clinical breast cancer · 2023Review
- Prediction of clinicopathological features, multi-omics events and prognosis based on digital pathology and deep learning in HRJournal of thoracic disease · 2023Article
- Big data in breast cancer: Towards precision treatment.Digital healthReview
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.