Other Cancers

An intelligent fusion model for Ki-67 prediction in non-small cell lung cancer: A cloud-based prediction system integrating radiomics.

BACKGROUND: The expression level of Ki-67 affects the prognosis of NSCLC patients. OBJECTIVE: Accurate preoperative prediction of Ki-67 expression in non-small cell lung cancer (NSCLC) is crucial for prognostic stratification. METHODS: This multicenter retrospective study enrolled 876 NSCLC patients (January 2015-December 2024) from four institutions, randomly divided into training (n = 525), test...

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth factor receptor 2 (HER2) is essential for managing breast cancer (BC) patients, as these biomarkers guide targeted therapies. Traditional methods such as immunohistochemistry (IHC) and in situ hybridisation (ISH) are widely used, but they are resource-intensive and time-consuming. To address these chal...

Estimate renal cell carcinoma recurrence rates using electronic health records.

BACKGROUND: Lack of readily available recurrence data has limited the use of electronic health records (EHR) for risk assessment of cancer recurrence ...

Deep Learning-Based Multimodal Fusion of Ultrasound, Cytology, and Clinical Features to Distinguish Follicular Thyroid Carcinoma from Adenoma: A Multicenter Study.

RATIONALE AND OBJECTIVES: Preoperative differentiation between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challen...

STC2-mediated calcium homeostasis dysregulation in the osteosarcoma microenvironment: Insights from single-cell sequencing and machine learning.

BACKGROUND: Osteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. Dysregulated calcium homeostasis may contribute to OS progressio...

Cross-task interpretability through unified modeling reveals a universal shortcut bias in neoantigen prediction.

Accurate neoantigen prediction is central to the design of personalized cancer immunotherapy. The immune recognition of neoantigens is a multi-step pr...

Imaging Immune Heterogeneity in Nasopharyngeal Carcinoma: A Multidimensional Radiomics Perspective.

RATIONALE AND OBJECTIVES: Nasopharyngeal carcinoma (NPC) is characterized by a distinctive virologic and immunologic profile, in which Epstein-Barr vi...

Multiclass Classification of Renal Tumor Subtypes: Addressing Diagnostic Challenges Using a Texture-Informed Deep Hybrid CNN-Transformer.

Accurate histopathological classification of renal cell carcinoma (RCC), along with its distinction from benign mimickers, is essential for precision ...

Exploration of the roles of SSR2 in hepatocellular carcinogenesis based on single-cell transcriptomics and spatial transcriptomics.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancer globally. However, HCC features poor prognosis due to complex pat...

Integrative multi-omics analysis identifies PAICS as a key regulator of epithelial-mesenchymal transition in breast cancer metastasis.

BACKGROUND: Breast cancer metastasis remains a major clinical challenge due to its complex molecular mechanisms, highlighting the need to identify key...

Development and validation of a multimodal AI-agent system for prognosis analysis of bladder urothelial carcinoma.

Precise survival risk stratification for bladder urothelial carcinoma (BUC) remains a clinical challenge. We developed and validated a multimodal AI a...

Breast area affects the performance of a commercial artificial intelligence algorithm assessment of negative digital breast tomosynthesis exams.

OBJECTIVE: To understand whether cancer-neutral image attributes (breast area and number of slices) impact an AI algorithm assessment of negative digi...

Evaluation of the impact of glycolysis-related gene signatures on prognosis and therapeutic targeting in lung adenocarcinoma.

Abnormal glycolysis is one of the hallmarks of cancer and plays a significant role in its progression. This study investigates the association between...

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characteri...

Interpretable prediction of occult lymph node metastasis in pancreatic ductal adenocarcinoma using a model fusing habitat radiomics and deep learning.

PURPOSE: To evaluate the value of integrating habitat radiomics features and deep learning features for predicting occult lymph node metastasis (OLNM)...

Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors.

Generative design and machine learning are increasingly prevalent in medicinal chemistry. To pilot the comprehensive use of automated molecular design...

Soft multiclass feature augmented deep learning to predict tumor origins using cytology or histology whole slide images.

Tailoring cancer treatment to the primary tumor site is essential for optimal outcomes, yet identifying the source of metastasis remains a significant...

Identification of a novel platelet-related prognostic model for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly lethal malignancy with high invasiveness and metastasis. Despite progress in its treatment, the high mortal...

Personalized neoantigen cancer vaccines: Why clinical benefit remains inconsistent.

Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen id...

Actinic keratosis staging in multimodal image data.

BACKGROUND AND OBJECTIVE: Actinic Keratosis (AK) is a common skin condition, usually appearing on sun-exposed areas, whose progression is associated w...