Other Cancers

Enhancing adverse drug event extraction and summarization for cancer drugs through large language models.

PURPOSE: Cancer treatments such as chemotherapy, targeted therapy, and immunotherapy can effectively combat malignant cells but frequently cause serious side effects by damaging healthy tissues. This underscores the need for robust Adverse Drug Event (ADE) reporting and summarization frameworks to improve patient safety, support clinical decision-making, and optimize treatment outcomes. METHODS: I...

Artificial intelligence for accurate tumor size assessment and non-invasive adenocarcinoma prediction in small-sized lung cancer.

INTRODUCTION: Accurate preoperative imaging is essential for improving the treatment of small lung cancers. Precise identification of non-invasive adenocarcinomas is critical for determining the suitability of sublobar resection. Conventional methodologies frequently demonstrate variability, particularly for small tumors or ground-glass nodules (GGNs). Artificial intelligence (AI) offers a consist...

The dual role of the crosstalk between autophagy and ferroptosis in lung cancer treatment: Advances in mechanisms and therapeutic strategies (Review).

The interaction between autophagy and ferroptosis has resulted in the identification of novel approaches for the treatment of lung cancer (LC). The tw...

Treatment of pulmonary fibrosis: From disease mechanisms to future novel therapies (Review).

Pulmonary fibrosis (PF) is a progressive and fatal interstitial lung disease characterized by irreversible lung scarring and frequently associated wit...

Nitenpyram promotes breast cancer progression via PARP1: Integration of multi-omics analyses with experimental validation.

Nitenpyram (NIT) is an insecticide used primarily for flea control in pets, especially cats and dogs. Some studies suggest that NIT is associated with...

Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.

Multiplexed Microenvironment-Responsive Probes Enable Rapid Glioblastoma Cell Line Analysis.

Accurate distinguishing the phenotype of glioblastoma (GBM) cell lines remains challenging in clinical diagnostics, particularly for rapid intraoperat...

The effect of neoadjuvant therapy on radiological, surgical, and pathological results in nonmetastatic breast cancer: A retrospective observational study.

The aim of the study was to evaluate the concordance between radiological imaging modalities and pathological findings and to test whether neoadjuvant...

The DNA-Based Disease Diagnosis Model with Strand Displacement Reaction.

MicroRNAs (miRNAs) serve as crucial biomarkers in disease diagnosis. Although silicon-based electronic machine learning models provide efficient means...

Development of a Classifier for Metabolic Subtypes of Nasopharyngeal Carcinoma to Guide Personalized Immunotherapy Strategies: Biomarker Analysis of the Phase III CONTINUUM and DIPPER Trials.

PURPOSE: Personalized immunotherapy strategies are urgently needed for patients with locoregionally advanced nasopharyngeal carcinoma (NPC). We aim to...

Radiomics-based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas (ROMUS): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer (MITO) study.

OBJECTIVE: To develop machine-learning models that incorporate clinical information and radiomics features extracted from ultrasound images to disting...

Fragmentomic liquid biopsy enables early breast cancer detection, molecular subtyping and lymph node assessment.

Breast cancer remains a leading global health concern in women, while screening is still limited by imaging accessibility and reduced sensitivity in d...

Integration of radiomics, deep learning, transcriptomics, and metabolomics reveals prognostic risk stratification and underlying biological mechanisms in colorectal cancer.

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide, yet current prognostic str...

Cell-free DNA methylome and fragmentome analysis for relapse monitoring of Ewing sarcoma.

Liquid biopsies and cell-free DNA (cfDNA) offer minimally invasive methods for the diagnosis and monitoring of Ewing Sarcoma (EwS). EwS have a low tum...

Integrated analysis of therapeutic strategies and prognostic factors in advanced lung adenocarcinoma: Retrospective study with emphasis on gene assays, multimodality treatment approaches and predictive machine learning models.

Patients with advanced lung adenocarcinoma have a range of treatment options, including targeted therapy and gene assay-guided chemotherapy. The aim o...

Context-Aware adaptive normalization LSTM (CAAN-LSTM) for immunotherapy decision support in cancer clinical data analysis.

BACKGROUND: Clinical decision-making for cancer immunotherapy is challenged by the heterogeneous and often incomplete nature of patient time-series da...

BCLC classification and AI-based image quantification: What is meant to be will come together - but how and when?: BCLC and AI-based image quantification.

The Barcelona Clinic Liver Cancer (BCLC) classification has been the mainstay for prognostic assessment and initial treatment selection in hepatocellu...

From Antigen to Atlas: A Multi-omics, Single-Cell Pipeline for Discovering Safe and Effective CAR Targets in Ovarian Cancer.

Chimeric antigen receptor (CAR) T-cell therapy has achieved remarkable success in hematologic malignancies but continues to face significant barriers ...

Artificial-intelligence-guided autophagy modulation and nanomedicine design for precision photodynamic cancer therapy.

Cancer remains a major cause of death worldwide and current therapies are often limited by toxicity, resistance and poor tumor selectivity. Photodynam...

Unraveling the connection between PFOA and bladder cancer: A study integrating network toxicology, molecular docking, and experimental validation.

PFOA, an environmental pollutant linked to bladder cancer, has unclear molecular mechanisms. Integrating transcriptomic data with network toxicology a...