Chemotherapy

Clinical relevance of the characterisation and quantification of CD8+ T-cell infiltration in high-grade serous ovarian carcinoma using machine learning-based image analysis of dual immunostaining.

INTRODUCTION: High-grade serous carcinoma (HGSC) is the most common and aggressive subtype of ovaria...

Challenges and Controversies in the Diagnosis and Management of Thymic Epithelial Tumors from the Thymic Tumor Subcommittee of the International Association for the Study of Lung Cancer Rare Tumors Committee.

Thymic epithelial tumors (TETs), comprising thymomas, thymic carcinomas, and thymic neuroendocrine n...

Quantitative CT Perfusion as a prognostic biomarker for chemotherapy response in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Response evaluation of pancreatic ductal adenocarcinoma (PDAC) with routine contrast-enh...

Artificial Intelligence in Personalized Breast Cancer Drug Safety: From Preclinical Toxicology to Clinical Risk Management.

PURPOSE: The artificial intelligence (AI) implementation in personalized medicine has transformed dr...

Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy.

Purpose To develop an explainable radio-pathomic graph deep-learning (RPGDL) system for multiscale s...

Deep learning for adaptive chemotherapy: A DDPG-based approach to optimizing tumor-immune dynamics.

In this article, we propose a deep reinforcement learning based chemotherapy regulation framework to...

Integrated Strategies for Nursing and Rehabilitation in Lung Cancer Patients.

This review delineates the pivotal role of nursing and rehabilitation in perioperative management an...

Predicting neoadjuvant therapy response in breast cancer from preoperative biopsy via spatial-semantic-differential learning and interpretable clinicopathological-guided fusion.

Predicting pathological complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer remain...

Clinical and immunological significance of FOXO1 as a biomarker of improved response to immune checkpoint plus tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma.

BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TK...

DSPONVNet: a multimodal deep learning model integrating intraoperative monitoring and clinical features for predicting postoperative nausea and vomiting risk.

Integrated spatial transcriptomics and pan-cancer XGBoost modeling uncover spatial drivers of immune exclusion and predict immunotherapy response.

Immunotherapy has revolutionized cancer treatment, yet characterizing the spatial complexity of the ...

Dosimetry Analysis of 177Lu-PSMA-I&T in Patients with Low-Volume Oligometastatic Hormone-Sensitive Prostate Cancer: A Secondary Analysis of the LUNAR Trial.

The phase 2 LUNAR trial randomized (1:1) patients with oligorecurrent hormone-sensitive prostate can...

Explainable machine learning to predict muscle loss during radiotherapy for oral cavity cancer.

BACKGROUND AND PURPOSE: Muscle loss during adjuvant radiotherapy is associated with poor survival ou...

Multimodality treatment and survival in primary cardiac malignancies: evidence from competing-risk and machine learning analyses.

BACKGROUND: Primary cardiac malignancies are rare and highly aggressive, with limited clinical evide...

Single-Cell Transcriptomic Analysis of Chemotherapy-Induced Changes in Osteosarcoma With a Pyroptosis-Related Gene-Based Prognostic Model.

Osteosarcoma, the most common primary malignant bone tumour, presents significant treatment challeng...

Arrhythmias and cardiac devices management in oncology patients.

Cardiac arrhythmia is increasingly encountered in patients with cancer, not only as a result of shar...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcom...

Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.

Neoantigens have emerged as central targets in the development of individualized cancer vaccines, as...

Machine learning identifies a 10-gene signature predicting hepatocellular carcinoma recurrence and immune-metabolic reprogramming.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality, with f...

PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway.

BACKGROUND: Glioblastoma (GBM), the most prevalent and aggressive primary brain tumor in adults, has...

Circulatory dietary and gut-derived metabolites predict early cognitive decline.

INTRODUCTION: A key component of disease prevention is the identification of at-risk individuals. Mi...