Other Cancers

Integration of 117 machine learning algorithms and single-cell transcriptomics identifies macrophage polarization and ER stress signatures for cancer prognosis and precision therapy.

BACKGROUND: Macrophage polarization and endoplasmic reticulum (ER) stress play critical yet incompletely understood roles in cancer progression and therapeutic resistance. METHODS: Here, we conduct a systematic pan-cancer analysis of macrophage polarization and ER stress-related genes (MPERSRGs) by integrating multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx),...

Integration of Single-Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma.

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular immunity-related prognostic genes in LUAD and propose novel strategies to improve its prognosis. LUAD-related datasets were obtained from public databases. Prognostic genes and a prognostic model were obtained through various bioinformatics analyzes, an...

Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.

Clear cell renal cell carcinoma (ccRCC) is distinguished by the absence of definitive diagnostic markers and efficacious treatment modalities, factors...

[Physiological age estimation model on pediatric panoramic radiographs based on machine learning and deep learning].

Objective: To automatically estimate children's physiological age from pediatric panoramic radiographs, employing a two-stage approach which involves ...

Multi omics and mechanistic investigation reveals CBFB as a prognostic biomarker in gastric cancer.

BACKGROUND: Gastric cancer is an aggressive malignancy with poor prognosis due to complex pathogenesis, underscoring the need for biomarkers and targe...

Genetically engineered human cell-based microrobots for selective cancer cell death.

Medical microrobots have strong potential for targeted therapeutic delivery; however, current systems achieve only physical targeting, and once at the...

Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...

The Negative Impact of a Non-Therapeutic Laparotomy in Patients With Inoperable Colorectal Peritoneal Metastases.

BACKGROUND: The peritoneum is the third most prevalent location for metastases of colorectal cancer. In patients with resectable disease, cytoreductiv...

Evaluating the interpretation of neck CT/MRI scans by ChatGPT-4V for detecting primary oropharyngeal squamous cell carcinoma: An exploratory study.

OBJECTIVES: Early and accurate detection of head and neck squamous cell carcinoma and the subset of oropharyngeal squamous cell carcinoma (OPSCC) is e...

Deep Learning for Pretreatment Imaging-Based Tumor and Nodal Classification in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Accurate pretreatment assessment of the extent of tumor invasion and status of cervical lymph node metastasis is essential for staging and...

Application of a machine learning-based PANoptosis-immune-related gene risk score model in prognostic stratification and immunotherapy benefit prediction for glioblastoma.

This study developed a risk score model using PANoptosis and immune-related genes to predict glioblastoma (GBM) prognosis. Utilizing TCGA data and 66 ...

Investigating the toxicological impacts of thiabendazole exposure on uterine corpus endometrial carcinoma utilizing network toxicology, machine learning, and molecular docking.

Uterine corpus endometrial carcinomas (UCEC) are common cancers of the female reproductive system linked to environmental chemicals. Thiabendazole (TB...

Multi-Institutional Annotated Multiparametric MRI Dataset of Pediatric High-Grade Gliomas.

Pediatric brain tumors are rare and still represent the most common solid tumors in children and the leading cause of cancer-related mortality in the ...

Radiomics-based outcome prediction for irinotecan-TACE in colorectal liver metastases: advanced analysis from the prospective CIREL trial.

OBJECTIVES: Transarterial chemoembolization (TACE) is a promising locoregional therapy for unresectable colorectal liver metastases, but patient selec...

Clinical validation and implementation of mSTOP, a machine learning-based, longitudinal prediction model for the early identification of non-small cell lung cancer patients who not benefit from immune checkpoint inhibitor treatment.

OBJECTIVES: There has been a lot of interest in the field of laboratory medicine regarding the use of machine learning (ML)-based prediction models. T...

Detection of Interpretable and Fine-Grained Brain Tumor Magnetic Resonance Imaging Based on Progressive Pruning: Machine Learning Model Development and Validation Study.

BACKGROUND: Brain tumor is one of the most malignant diseases of the central nervous system, and early accurate detection is of great significance for...

An advanced hybrid deep learning framework for high-precision brain tumor detection and classification in MRI scans.

Early and accurate identification of brain tumors from magnetic resonance imaging (MRI) is essential for timely clinical intervention; however, manual...

An agentic framework for autonomous scientific discovery in cancer pathology.

Artificial intelligence has advanced cancer pathology, but many systems still depend on hand-crafted features, are hard to explain and rely on fragmen...

Capturing "source" and "evolution": A 5-year recurrence risk prediction model for nasopharyngeal carcinoma based on integrated radiomic spatial heterogeneity of primary tumor and lymph nodes.

OBJECTIVE: This study aims to deeply mine the radiomic features of the primary tumor (GTVp) and cervical metastatic lymph nodes (GTVn) in nasopharynge...

Cheminformatics analysis, machine learning-based QSAR model building and virtual screening: identification of dual ROCK1 and TGFBR1 inhibitors for the treatment of cancer metastasis.

Rho-associated coiled-coil kinase 1 (ROCK1) and Transforming Growth Factor Beta Receptor 1 (TGFBR1) are pivotal mediators of epithelial-mesenchymal tr...