Other Cancers

Multiple Instance Learning for the Detection of Lymph Node and Omental Metastases in Carcinoma of the Ovaries, Fallopian Tubes and Peritoneum.

: Surgical pathology of tubo-ovarian and peritoneal cancer carries a well-recognised diagnostic workload, partly due to the large amount of non-primary tumour-related tissue requiring assessment for the presence of metastatic disease. The lymph nodes and omentum are almost universally included in such resection cases and contribute considerably to this burden, principally due to volume rather than...

Baseline Radiomics as a Prognostic Tool for Clinical Benefit from Immune Checkpoint Inhibition in Inoperable NSCLC Without Activating Mutations.

Checkpoint inhibitors (ICIs) are key therapies for NSCLC, but current selection criteria, such as excluding mutation carriers and assessing PD-L1, lack sensitivity. As a result, many patients receive costly treatments with limited benefit. Therefore, this study aimed to predict which NSCLC patients would achieve durable survival (≥24 months) with immunotherapy. A comprehensive ensemble radiomics...

AI-based multimodal prediction of lymph node metastasis and capsular invasion in cT1N0M0 papillary thyroid carcinoma.

BACKGROUND: Accurate preoperative evaluation of cT1N0M0 papillary thyroid carcinoma (PTC) is essential for guiding appropriate treatment strategies. A...

Subregion-based radiomics analysis for predicting the histological grade of clear cell renal cell carcinoma.

PURPOSE: We explored the feasibility of constructing machine learning (ML) models based on subregion radiomics features (RFs) to predict the histologi...

Multilevel Inter-modal and Intra-modal Transformer network with domain adversarial learning for multimodal sleep staging.

Sleep staging identification is a fundamental task for the diagnosis of sleep disorders. With the development of biosensing technology and deep learni...

Machine learning-driven prognostic model based on sphingolipid-related gene signature in pancreatic cancer: development and validation.

BACKGROUND: Pancreatic cancer, a highly malignant tumor with poor prognosis, lacks effective early diagnosis and treatment strategies. Sphingolipids h...

Multimodal integration of longitudinal noninvasive diagnostics for survival prediction in immunotherapy using deep learning.

OBJECTIVES: Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced cancer...

Multiomics in Renal Cell Carcinoma: Current Landscape and Future Directions for Precision Medicine.

PURPOSE OF REVIEW: Renal cell carcinoma (RCC) is a prevalent and increasingly diagnosed malignancy associated with high mortality and recurrence rates...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage...

A novel fractional computational neural framework for analyzing cancer model under chemotherapy drug.

In this study, a novel Caputo fractional-order model is proposed to represent the complex interactions among stem cells, effector cells, and tumor cel...

From development to implementation: a systematic review on the current maturity status of artificial intelligence models for patients with colorectal cancer liver metastases.

Introduction Artificial intelligence (AI) is increasingly being researched and developed in the medical field and holds potential to transform healthc...

Radiomics based on dual-energy CT for noninvasive prediction of cervical lymph node metastases in patients with nasopharyngeal carcinoma.

INTRODUCTION: To develop and validate a machine learning model based on dual-energy computed tomography (DECT) for predicting cervical lymph node meta...

Deep learning model for malignancy prediction of TI-RADS 4 thyroid nodules with high-risk characteristics using multimodal ultrasound: A multicentre study.

The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in reducing missed and misdiagnosed cases in clinical pr...

Radiomics-Based Classification of Clear Cell Renal Cell Carcinoma ISUP Grade: A Machine Learning Approach with SHAP-Enhanced Explainability.

: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer, and its prognosis is closely linked to the International Society...

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks.

Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequences to enhance immunotherapy predictability and eff...

A Domain-Specific Pretrained Model for Detecting Malignant and Premalignant Ocular Surface Tumors: A Multicenter Model Development and Evaluation Study.

Malignant and premalignant ocular surface tumors (OSTs) can be sight-threatening or even life-threatening if not diagnosed and treated promptly. Artif...

The development of predictive biomarkers and immunologic markers for breast cancer: current status and future perspectives.

Breast cancer is the leading cause of cancer-related mortality among women worldwide. The development of predictive biomarkers and immunologic markers...

Leveraging multiple cell-death patterns based on machine learning to decipher the prognosis, immune, and immune therapeutic response of soft tissue sarcoma.

Soft tissue sarcomas (STS) imposes a substantial healthcare burden on society. The progression of these tumors is significantly influenced by diverse ...

MobNas ensembled model for breast cancer prediction.

Breast cancer poses a real and immense threat to humankind, thus a need to develop a way of diagnosing this devastating disease early, accurately, and...

Multidimensional Evidence Chain of Nutritional Impact on Digestive System Tumors: Integration of Mendelian Randomization Causal Inference, NHANES Epidemiological Data, and Transcriptomic Analysis.

BACKGROUND: The global burden of digestive system tumors (e.g., hepatocellular carcinoma, gastric cancer, colorectal cancer) continues to rise, with l...