Other Cancers

ROI-guided virtual narrow band imaging for laryngeal cancer screening.

White light laryngoscopy is widely available but can miss subtle vascular changes associated with early laryngeal neoplasia. We developed a region-of-interest (ROI)-guided cycle-consistent generative adversarial network (CycleGAN) that translates white light imaging (WLI) images into virtual narrow band imaging (NBI) images, while emphasizing expert-annotated lesion regions. The framework was trai...

Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN99301435).

BACKGROUND: The integration of clinical decision support tools in medical practice is challenging and must be carefully undertaken, especially in cancer management. Noninvasive Lymph Node Status (NILS) is a web-based tool designed to estimate the probability of benign axillary lymph nodes in female patients with breast cancer scheduled for primary surgery. The aim was to identify barriers to NILS ...

Artificial Intelligence in Hospice and Palliative Care: A Systematic Review of Its Role in Interprofessional Shared Decision-Making Care.

BackgroundArtificial intelligence (AI) is increasingly integrated into hospice and palliative care to support clinical decision-making across clinicia...

Quantum-inspired optimization of transformer-capsule networks for accurate brain tumor segmentation and classification.

Brain tumors represent one of the deadliest types of neurological diseases, a fact that makes early accurate diagnosis essential for the survival of p...

Lactylation-related prognostic signature characterized in pancreatic ductal adenocarcinoma through public scRNA-seq dataset and machine learning algorithms: the TOP2A-H3K18la-NQO1 axis orchestrates malignant progression.

BACKGROUND: Lactate promotes histone lactylation, which affects protein transcription and translation, thereby influencing tumour cell progression. Ho...

Artificial intelligence in cancer immunotherapy: current trends in predicting response and personalizing treatment.

Artificial intelligence (AI) can transform cancer immunotherapy by enabling more accurate prediction of treatment responses, the discovery of specific...

Artificial intelligence and transforming cancer care.

Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized app...

Colorectal cancer sidedness: prognostic implications and the predictive role of artificial intelligence.

BACKGROUND: Colorectal cancer (CRC) is a biologically heterogeneous disease in which tumor sidedness has emerged as a relevant prognostic factor. Conv...

Assessing biomarkers for patients with breast cancer who are suited for adjuvant therapy.

INTRODUCTION: Biomarker-guided stratification is essential for optimizing adjuvant systemic therapy in early-stage breast cancer, requiring a balance ...

Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac Dysfunction.

BACKGROUND: Predicting risk of cancer therapy-related cardiac dysfunction (CTRCD) remains challenging. OBJECTIVES: The purpose of this study was to as...

Advances in Digital Pathology and Artificial Intelligence in the Diagnosis of Myeloid Neoplasms.

Recent advances in digital pathology and artificial intelligence (AI) are transforming our ability to diagnose myeloid neoplasms, including acute myel...

Tree-based and sparse logistic models for predicting one-month postoperative performance status after surgery for spinal metastases.

PURPOSE: We aimed to develop and internally validate prediction models for one-month postoperative performance status (PS) after surgery for spinal me...

Review of systemic therapy in HCC with an approach to response assessment in clinical practice.

Systemic therapy for hepatocellular carcinoma (HCC) has undergone rapid transformation over the past decade, significantly expanding treatment options...

Predicting late radiation-associated neurocognitive and endocrine toxicity in patients with brain tumors.

PURPOSE: Neurocognitive and endocrine dysfunction are potential complications of cranial irradiation. However, risk factors are poorly understood, imp...

RAS pathway activity subtypes identified by machine learning define prognostic and immune microenvironment characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, remains a leading cause of cancer-related ...

Deep learning and radiomics models in patients with advanced non-small cell lung cancer treated with immunotherapy combined with stereotactic radiotherapy.

Quantitative imaging is an emerging field that may allow prediction of oncological outcomes. We investigate whether radiomics and deep learning can pr...

Machine learning-based prediction of hepatocellular carcinoma risk in steatotic liver disease: A nationwide cohort study.

BACKGROUND AND AIMS: Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of...

Nanomedicine-based cancer immunotherapy: translational barriers, mechanistic strategies, and future perspectives.

Nanomedicine-based cancer immunotherapy integrates nanotechnology with immune modulation, representing a promising strategy to improve both the effica...

Advances in immune checkpoint inhibitor therapy for microsatellite instability-high (MSI-H) and mismatch repair-deficient (dMMR) colorectal cancer: Insights from the tumor immune microenvironment.

This review systematically analyzes the relationship between the immune microenvironment characteristics of microsatellite instability-high (MSI-H) or...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...