Other Cancers

Loss of biomechanical features reveals smooth muscle disruption and disease progression in prostate cancer.

BACKGROUND: Biomechanical features show notable heterogeneity in tumor risk stratification, yet their role in prostate cancer (PCa) progression remains unclear. This study aimed to elucidate the role and underlying mechanism of biomechanical features in PCa progression. METHODS: We integrated transcriptomic data from 1693 PCa patients across ten public cohorts and single-cell RNA sequencing (scRNA...

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood and have an extremely high cumulative risk to develop cancer during their lifespan. Myeloid malignancy is one of the main neoplastic risks for patients with FA, including high-risk myelodysplastic syndrome (MDS), recently renamed as myelodysplastic ...

Leveraging machine learning to predict de novo skin malignancy following lung transplantation.

AIMS: This study aimed to predict post-transplant malignancy risks at multiple levels among lung transplant recipients using machine learning (ML) and...

Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.

OBJECTIVE: To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incid...

The Potential of Ensemble-Based Automated Sleep Staging on Single-Channel EEG Signal From a Wearable Device.

Machine-learning-based sleep staging models have achieved expert-level performance on standard polysomnographic (PSG) data. However, their application...

Multimetallic nanostructures: innovations and applications in environmental remediation, biosensing, and medical technologies.

Multimetallic nanostructures (MNs) have emerged as versatile materials with significant potential in various applications, including environmental rem...

Artificial Intelligence-assisted Risk Stratification of Thyroid Nodules with Atypia of Undetermined Significance.

OBJECTIVE: Given the limitations of conventional approaches in managing indeterminate thyroid nodules, there remains an unmet need for non-invasive as...

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly wh...

Hybrid imaging-clinical model for predicting microvascular invasion in hepatocellular carcinoma using deep learning-derived features from CT.

The role of adipose tissue in predicting microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains unclear. This study prop...

Machine Learning for Predicting Malignant Transformation in Actinic Cheilitis: A Prognostic Support System Based on Demographic and Clinical Descriptors.

OBJECTIVE: This study aimed to develop and evaluate Machine Learning models to predict the malignant transformation (MT) in patients with actinic chei...

Deep visual detection system for oral squamous cell carcinoma.

BACKGROUND: Oral Squamous Cell Carcinoma (OSCC) is a widespread and aggressive malignancy where early and accurate detection is essential for improvin...

Multiparametric MRI radiomics nomogram predicts synchronous distant metastasis in rectal cancer.

This study aimed to evaluate the utility of a multiparametric MRI-based radiomics nomogram for identifying patients with rectal cancer (RC) at high ri...

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer.

BACKGROUND: Accurate preoperative staging is critical for improving the prognosis, treatment, and survival outcomes of epithelial ovarian cancer (EOC)...

SERPINA1 as a Shared Biomarker in Periodontitis and Oral Squamous Cell Carcinoma.

OBJECTIVE: Periodontitis (PD) and oral squamous cell carcinoma (OSCC) frequently co‑occur in clinical populations. However, shared molecular determina...

Integrated multi-omics analysis of prognostic model and immune microenvironment in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive malignancy originating from the epithelial lining of second-order bile ducts. Desp...

Comment on "leveraging readily available clinical data with machine learning to predict first-line immunotherapy outcomes in non-small cell lung Cancer".

Peripheral Nerves in Cancer: Regulatory Roles and Therapeutic Strategies.

Cancer neuroscience has emerged as a transformative frontier in oncology research, focusing on the interplay between cancer cells and the nervous syst...

Deciphering the molecular landscape of Sjögren's disease, mucosa-associated lymphoid tissue lymphoma, and thyroid cancer: unraveling the complexities of disease mechanisms and diagnostic biomarkers.

BACKGROUND: Sjögren's disease (SjD), mucosa-associated lymphoid tissue lymphoma (MALT lymphoma), and thyroid cancer (THCA) are clinically distinct yet...

Machine learning integrating MRI and clinical features predicts early recurrence of hepatocellular carcinoma after resection.

This study aims to construct a robust artificial intelligence (AI) model to predict early recurrence of hepatocellular carcinoma (HCC) following surgi...