Skin Cancer

Interactive active learning for literature screening: finetuning GPT with DeepSeek reasoning for cross-domain generalization.

OBJECTIVE: Automated literature screening in biomedical research is often hindered by domain shifts and scarcity of labeled data, which limit model accuracy and generalizability. While large language models (LLMs) perform well in zero-shot settings, they often fail to capture complex, domain-specific reasoning patterns. To address this limitation, this study investigates whether an interactive, we...

Integration Analysis of Bayesian and Machine Learning for Heterogeneity, Biomarkers, and Optimal Combination Regimens of Pucotenlimab in Solid Tumors.

The efficacy of PD-1 inhibitor pucotenlimab (HX008) in solid tumors exhibits heterogeneity. This study integrated data from 6 clinical trials (covering gastric/gastroesophageal junction cancer, triple-negative breast cancer, melanoma, and dMMR/MSI-H solid tumors) using Bayesian meta-analysis, machine learning (optimal XGBoost AUC = 0.86), and network meta-analysis to construct an integrated "effic...

Clinical Significance of Biomarkers in Oropharyngeal Squamous Cell Carcinoma: Recurrence Prediction and Treatment Response.

BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) accounts for a substantial proportion of head and neck cancers, with a rising incidence larg...

Early ctDNA stratifies survival in locally advanced and oligometastatic lung cancer treated with radiotherapy.

PURPOSE: Circulating tumor fraction estimate (ctFE) is a machine learning-derived composite metric of circulating tumor DNA (ctDNA) burden. We hypothe...

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 imm...

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...

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...

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 ...

Integrating single-cell transcriptomics and machine learning to predict breast cancer prognosis and immunotherapy sensitivity: a study based on proliferating T cells.

Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis despite current treatment modalities. This study aimed...

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apopto...

Reinventing miRNA cancer therapy through immunomodulation and AI.

Despite the rational therapeutic premise of microRNA (miRNA) replacement or inhibition for cancer treatment, its clinical translation remains signific...

A macrophage co-expression signature enables robust prognostic prediction in glioblastoma.

BACKGROUND: Glioblastoma (GBM) exhibits profound cellular heterogeneity and a highly immunosuppressive microenvironment in which tumor-associated macr...

3D-printed real-time biosensing system integrating deep learning for label-free in vitro T cell culture analysis.

Recent advances in T cell-based immunotherapies highlight the urgent need for precise and dynamic monitoring across the entire cell culture pipeline. ...

Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.

Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has...

Three-dimensional oxygen maps of tumors in real time - Analysis in the context of active tumor vasculature.

BACKGROUND AND OBJECTIVE: Characterizing the tumor microenvironment (TME) requires integrating multiple physiological features, including oxygenation,...

Deep Learning and Experimental Validation of BRCA1-Associated Protein-1 Missense Variant Pathogenicity in Uveal Melanoma.

OBJECTIVE: To benchmark the pathogenicity predictions of AlphaMissense, a deep learning model, against high-throughput functional scores from saturati...

Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.

Radiotherapy (RT) remains a cornerstone of cancer management but is fundamentally constrained by normal tissue toxicity, intrinsic and acquired radior...

Crosstalk between immune and programmed cell death and their application in colorectal cancer risk stratification.

Programmed cell death (PCD) and cellular immunity play pivotal roles in colorectal cancer (CRC) progression; understanding their crosstalk and identif...

Optimal treatment selection for hepatocellular carcinoma in the era of immunotherapy.

Immunotherapy has revolutionized hepatocellular carcinoma (HCC) management, necessitating personalized strategies in current guidelines. Despite curat...