Other Cancers

Machine learning-based radiomics analysis in enhancing CT for predicting pathological subtypes and WHO staging of thymic epithelial tumors: a multicenter study.

This study is aimed to develop predictive models for classifying thymic epithelial tumor (TET) histological subtypes (A/AB/B1, B2/B3, C) and WHO stages (I-IV) using radiomics features derived from contrast-enhanced CT scans. These models were validated on multicenter external datasets to improve preoperative diagnosis and guide treatment decisions. A total of 257 patients diagnosed with TET betwee...

Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits pronounced heterogeneity, which significantly limits the effectiveness of precision therapies. A comprehensive understanding of the biological characteristics and molecular mechanisms underlying HCC cell subpopulations is crucial for improving prognostic predictions and refining treatment strategies.

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tu...

National Guidelines for Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in Peritoneal Malignancies: A Worldwide Systematic Review and Recommendations of Strength Analysis.

BACKGROUND: National guidelines (GLs) for surgical cytoreduction (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) in the management of peri...

Integrative multi-omics reveal NSUN2 facilitates glycolysis and histone lactylation-driven immune evasion in renal carcinoma.

Clear cell renal carcinoma (ccRCC) is the most prevalent and aggressive subtype of kidney cancer. Targeting ccRCC metabolism is a promising therapeuti...

Multimodal Explainable Artificial Intelligence for Prognostic Stratification of Glioblastoma Patients.

Glioblastoma is the most common and aggressive malignant adult tumor of the central nervous system, with a grim prognosis and heterogeneous morphologi...

MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.

Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pivotal role in ensuring effective treatment and enh...

Learnable prototype-guided multiple instance learning for detecting tertiary lymphoid structures in multi-cancer whole-slide pathological images.

Tertiary lymphoid structures (TLS) are ectopic lymphoid aggregates that form under specific pathological conditions, such as chronic inflammation and ...

POCALI: Prediction and Insight on CAncer LncRNAs by Integrating Multi-Omics Data with Machine Learning.

Long non-coding RNAs (lncRNAs) are receiving increasing attention as biomarkers for cancer diagnosis and therapy. Although there are many computationa...

Construction and Multi-dimensional Validation of a Lactylation-Related Signature for Glioblastoma Multiforme Prognostic and Therapeutic Purposes.

Glioblastoma multiforme, one of the most malignant types of brain tumor, heavily relies on glycolytic pathways and is significantly influenced by immu...

Unveiling the role of IL7R in metabolism-associated fatty liver disease leading to hepatocellular carcinoma through transcriptomic and machine learning approaches.

Dysregulation of hepatic metabolism is a crucial factor in the development of fatty liver disease and significantly increases the risk of hepatocellul...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...

SSC-SleepNet: A Siamese-Based Automatic Sleep Staging Model with Improved N1 Sleep Detection.

Automatic sleep staging from single-channel electroencephalography (EEG) using artificial intelligence (AI) is emerging as an alternative to costly an...

Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Despit...

Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.

Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appe...

Multimodal fusion model for prognostic prediction and radiotherapy response assessment in head and neck squamous cell carcinoma.

Accurate prediction of prognosis and postoperative radiotherapy response is critical for personalized treatment in head and neck squamous cell carcino...

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study.

OBJECTIVES: Pancreatic cancer treatment plans involving surgery and/or chemotherapy are highly dependent on disease stage. However, current staging sy...

Integrative machine learning model for subtype identification and prognostic prediction in lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) is a leading cause of cancer-related mortality, and tumor heterogeneity could result in diverse progno...

Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflow.

OBJECTIVES: For patients with colorectal liver metastases (CRLM), total tumor volume (TTV) is prognostic. A deep-learning segmentation model for CRLM ...

[Psilocybin in the setting of treatment-resistant unipolar depression: A case report].

BACKGROUND: Current antidepressants have shown certain limitations in the treatment of unipolar depression. Their long onset of action, interactions, ...