Other Cancers

An explainable radiomics model based on multiparametric magnetic resonance for differentiating benign and malignant orbital tumors.

OBJECTIVE: To develop and internally test a multiparametric radiomics combined model for differentiating benign and malignant orbital tumors. PATIENTS AND METHODS: This retrospective study analyzed 147 patients from two centers (December 2014 to March 2024) with pathologically confirmed orbital tumors and preoperative contrast-enhanced magnetic resonance imaging(MRI). After image preprocessing, 36...

A Multicenter Study on Deep Learning Model-Assisted Detection of Brain Metastases in MR Images.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a deep learning-based brain metastasis detection model (BMDM) in magnetic resonance images for diagnosing brain metastases (BMs). MATERIALS AND METHODS: We retrospectively collected data from 950 patients serving as the training and test sets for developing BMDM and from an additional 423 patients as the validation set. Three readi...

Design of novel PI3Kα and PI3Kγ inhibitors for cancer treatment using pharmacophore, protein-ligand contacts, and machine learning methods.

Cancer is a complex disease characterised by the unregulated growth of abnormal cells. The intracellular signaling pathway, specifically phosphatidyli...

Overview of combined adjuvant strategies for tumor biomarker detection.

Cancer is one of the leading causes of death worldwide, and early tumor detection can significantly reduce mortality rates. Liquid biopsy is a minimal...

Loop of N2-polarized neutrophils and exhausted CD8 + T cells induces immunotherapy resistance in NSCLC.

While neutrophils represent a prominent myeloid component in non-small cell lung cancer (NSCLC), the specific immunosuppressive functions of N2-polari...

Integrating Generative AI into Nomograms for Breast Cancer Nodal Risk Predictions.

BACKGROUND: Nomograms predicting the likelihood of sentinel lymph node (SLN) metastasis in early-stage breast cancer can aid surgical decision-making ...

Microrobotic copper-rich electrochemical interfacing for targeted cancer theranostics in the gut.

The exquisite spatiotemporal regulation of drug biodistribution is paramount for optimal targeted cancer theranostics. Robotic ingestible devices prom...

Correction: Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Lung cancer as a global health challenge: Multidimensional biomarker research and therapeutic advances.

Lung cancer, the leading cause of global cancer-related mortality, is categorized into small-cell and non-small-cell subtypes. The heterogeneous non-s...

Immune-activated & pathology-characterized: the distinct clear cell renal cell carcinoma subtypes for 3PM strategies derived from artificial intelligence in multi-omics.

BACKGROUND AND OBJECTIVE: Renal clear cell carcinoma (ccRCC) is highly heterogeneous, with significant differences in clinical outcomes such as progno...

Based on WGCNA and machine learning studies, SMURF2 drives NSCLC malignant transformation, ferroptosis, and macrophage polarization by ubiquitinating SPP1.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with poor prognosis and high mortality in advanced stages. Although sec...

AI in the Prediction of Hepatic Fibrosis Progression Using Non-Coding RNAs.

Hepatic fibrosis is a dynamic and progressive condition that can lead to cirrhosis and hepatocellular carcinoma (HCC) if left untreated. Appropriate a...

Cardiogenic Shock Revisited: From Hemodynamic-Centric to Multimodal Precision Care.

Cardiogenic shock (CS) remains a major clinical challenge, with persistently high short-term mortality despite advances in reperfusion therapy, pharma...

Machine Learning Algorithm for Nanomedicine: AI Curated Nanocarriers for Cancer Treatment.

Cancer remains a major global health challenge due to its genetic variability and intricate molecular mechanisms, which complicate the development of ...

Cross-cancer survival prediction using machine learning models.

Among the many challenges faced by healthcare systems, cancer remains one of the most urgent. This makes the application of artificial intelligence a ...

Detection of Lung and Colon Cancer Using XRx-Net With Histopathological Images.

Lung and Colon Cancer (LCC) is a prevalent type of cancer influenced by factors such as genetics, smoking, second-hand smoke exposure, and alcohol con...

Predicting the Postoperative Recurrence Risk in Soft-Tissue Sarcomas of the Extremities and Trunk Using MRI-Based Nomogram.

RATIONALE AND OBJECTIVES: This study aims to develop a comprehensive nomogram for predicting the 3-year recurrence risk of patients with soft-tissue s...

Clinically interpretable nomogram combining body composition and clinicopathological features for one year survival prediction in advanced solid tumors.

Immune checkpoint inhibitors (ICIs) have improved outcomes for patients with solid tumors, but reliable predictors of overall survival (OS) are limite...

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which ca...

From Multimodal Data to Clinical Insight: An Explainable Model for Preoperative Salivary Gland Lesion Diagnosis.

OBJECTIVE: To develop and validate a multimodal dual-step support vector machine model (SVM-DualNet) for the preoperative three-class classification o...