ArticleCell reports. Medicine2024
Next-generation lung cancer pathology: Development and validation of diagnostic and prognostic algorithms.
Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Improving neoadjuvant and perioperative therapy in non-small-cell lung cancer.Nature reviews. Clinical oncology · 2026Review
- Multimodal integration of pathomics and clinical features improves recurrence risk prediction in pediatric medulloblastoma.Pediatric research · 2026Article
- An agentic framework for autonomous scientific discovery in cancer pathology.Nature medicine · 2026Article
- Autonomous pathology research using agentic AI shows potential in oncology.Nature medicine · 2026Article
- Comprehensive evaluation of cross cancer generalization in histopathology segmentation models across 21 tumor types.Communications medicine · 2026Article
- Deep learning-driven recognition of panoramic tumor microenvironment features in H&E sections and its application.Journal for immunotherapy of cancer · 2026Review
- Artificial Intelligence in Lung Cancer: A Narrative Review of Recent Advances in Diagnosis, Biomarker Discovery, and Drug Development.Pharmaceutics · 2026Review
- Applications of AI/ML in accelerating the development of pulmonary drug delivery system.Acta pharmaceutica Sinica. B · 2026Review
- TNM staging of esophageal cancer using fine-tuned pathology foundation models and multiple instance learning.Frontiers in oncology · 2026Article
- Automating tumor-stroma ratio quantification in colon cancer patients from the UNITED study.ESMO open · 2026Article
- Thoracic ultrasonography-guided biopsy: Radiological and radiometabolic factors affecting diagnostic success.Northern clinics of Istanbul · 2026Article
- Similarity-guided swarm of models: enhancing semi-supervised learning in computational pathology.Scientific reports · 2025Article
- Applications of artificial intelligence in non-small cell lung cancer: from precision diagnosis to personalized prognosis and therapy.Journal of translational medicine · 2025Review
- Multimodal pathomics and clinical features predict postresection permanent hydrocephalus in pediatric medulloblastoma.Journal of neuro-oncology · 2025Article
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- Accurate prediction of disease-free and overall survival in non-small cell lung cancer using patient-level multimodal weakly supervised learning.NPJ precision oncology · 2025Article
- A Need for Multi-Institutional Collaboration for Deep Learning-Driven Assessment of Osteosarcoma Treatment Response.The American journal of pathology · 2025Article
- Review
- GrandQC: A comprehensive solution to quality control problem in digital pathology.Nature communications · 2024Article
Corrections and comments
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors. In this study, we develop a clinically useful computational pathology platform for NSCLC that can be a foundation for multiple downstream applications and provide immediate value for patient care optimization and individualization. We train the primary multi-class tissue segmentation algorithm on a substantial, high-quality, manually annotated dataset of whole-slide images with lung adenocarcinoma and squamous cell carcinomas. We investigate two downstream applications. NSCLC subtyping algorithm is trained and validated using a large, multi-institutional (n = 6), multi-scanner (n = 5), international cohort of NSCLC cases (slides/patients 4,097/1,527). Moreover, we develop four AI-derived, fully explainable, quantitative, prognostic parameters (based on tertiary lymphoid structure and necrosis assessment) and validate them for different clinical endpoints. The computational platform enables the high-precision, quantitative analysis of H&E-stained slides. The developed prognostic parameters facilitate robust and independent risk stratification of patients with NSCLC.
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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.