Other Cancers

Nanoparticle-based mechanistic and multifunctional strategies for targeted osteosarcoma therapy.

Osteosarcoma is the most common malignant bone tumor in children and adolescents, usually affecting the long bones of the limbs. Despite progress in surgery, chemotherapy, and radiotherapy, patient outcomes remain poor, highlighting the need for better treatments. Nanoparticles have emerged as promising platforms for targeted osteosarcoma therapy, offering selective drug delivery, controlled relea...

A vision-language foundation model improves preoperative diagnosis of follicular thyroid neoplasms using ultrasound images.

Preoperative discrimination between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challenging, as imaging and cytological approaches often show limited efficacy. Even fine-needle aspiration (FNA) biopsy and intraoperative frozen sections frequently fail to provide conclusive results. Thus, follicular thyroid neoplasms (FNs) typically necessitate complete surgical ...

MUSIOMICS: A multi-region radiomics framework that outperforms single-region analysis in classifying malignant pulmonary nodules.

BACKGROUND AND OBJECTIVE: Radiomic studies in lung cancer have primarily analyzed single-domain features extracted separately from intranodular (Zone-...

Assessment of high- and low-risk histopathologic subtypes of basal cell carcinoma using artificial intelligence and dermatologist evaluation.

BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, and accurate histopathologic risk stratification is essential for treatment sel...

From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chron...

Diagnostic performance of deep learning models on ultrasound images for distinguishing benign from malignant ovarian cysts.

BACKGROUND: Ovarian cysts are a common pelvic disorder in women, and accurate differentiation between benign and malignant types is essential for guid...

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

Recent Advances in Analytical Techniques for Cancer Diagnostics and Therapeutics: Combining State-of-the-Art Technologies for Precision Oncology.

Cancer remains a leading global health challenge, necessitating continuous advancements in diagnostics and therapeutics to enhance patient outcomes. A...

Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often exhibits limited responsiveness to immune checkpoint inhibitors (ICIs), largely due to an immunosuppressive tumor...

A Preliminary Study of a Machine Learning Prediction of Poorly Differentiated Hepatocellular Carcinoma Based on a Comprehensive Parameter Analysis Using Dual-Energy Computed Tomography.

OBJECTIVE: To develop and evaluate the performance of a predictive machine learning model for poorly differentiated hepatocellular carcinoma (p-HCC) u...

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantit...

Augmenting Large Language Model With Prompt Engineering and Supervised Fine-Tuning in Non-Small Cell Lung Cancer Tumor-Node-Metastasis Staging: Framework Development and Validation.

BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). Ho...

Deep Learning-Based Contrast-Enhanced Ultrasound for Ki-67 Assessment and Prognosis in Hepatocellular Carcinoma.

Ki-67 is a critical prognostic marker for hepatocellular carcinoma (HCC), yet its clinical assessment relies on invasive biopsy. This study aimed to d...

Brain tumors classification using electrical bioimpedance spectroscopy based on a multi-scale feature extraction network with frequency band attention mechanism.

Electrical bioimpedance (EBI) measurement provides insights into the biophysical properties of tissues, offering valuable information for tumor diagno...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

A deep learning-based digital biopsy for predicting early recurrence in gastric cancer.

Early postoperative recurrence is a major cause of treatment failure in patients with locally advanced gastric cancer (LAGC), yet current staging syst...

Decoding immunotherapy response through computational modeling.

Immunotherapy has seen success in treating patients with cancer, but variable responses underscore the need for effective patient stratification and t...

AI-Generated Clinical Images of Head-and-Neck Lesions in Plastic Surgery Education: An Expert Evaluation.

BACKGROUND: Clinical images are essential in plastic and reconstructive surgery education, particularly for understanding pathology, planning reconstr...

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE) remains a leading cause of early death and profou...

Convergence of multiplexed immunosensors, nanotechnology, and AI for early pancreatic cancer diagnosis.

Pancreatic cancer (PC) remains one of the deadliest malignancies, largely because of its asymptomatic onset, rapid progression, and absence of sensiti...