Chemotherapy

Multi-Omics Analysis Identifies Paxillin as a Biomarker of Doxorubicin Resistance via Cytoskeletal Remodeling and Immune Exhaustion.

Chemotherapy resistance remains a primary cause of treatment failure in breast cancer, yet the global proteomic landscape driving this phenotype has not been completely understood. In this study, we employed a systematic multiomics approach, integrating quantitative proteomics of doxorubicin-resistant cells with transcriptomic and proteomic data from large-scale clinical cohorts (TCGA and FUSCC). ...

Predicting PPOI secondary to laparoscopic radical resection of rectal cancer combined with lobaplatin hyperthermic intraperitoneal chemotherapy: a multi-center study.

PURPOSE: PPOI is one of the common complications of intraperitoneal hyperthermic chemotherapy during laparoscopic radical resection of rectal cancer, which seriously affects the prognosis of patients. The purpose of this study is to establish a prediction system for PPOI secondary to laparoscopic radical resection of rectal cancer combined with intraperitoneal hyperthermic chemotherapy with lobapl...

A Highly Sensitive, Ultrawide-Range Temperature-Pressure Dual-Mode Sensing Platform for Battery Health and Marine Monitoring.

Dual-mode sensors with ultrahigh sensitivity, wide detection range, linearity, and stable temperature response are highly desirable for monitoring in ...

Predicting early-stage breast cancer disease-free survival and adjuvant therapy benefit from multimodal information using deep learning.

Accurate prediction of disease-free survival (DFS) is essential for tailoring adjuvant regimens and improving clinical outcomes in early-stage breast ...

Radiomics-based unsupervised clustering and deep learning nomogram for response prediction after neoadjuvant chemotherapy in locally advanced laryngeal cancer.

OBJECTIVES: To develop a nomogram model for individualized prediction of neoadjuvant chemotherapy (NAC) response in locally advanced laryngeal cancer ...

Machine learning model based on clinical and imaging features for predicting fungal infections in children with leukemia.

BACKGROUND: Due to immunosuppression, mucosal barrier injury, and prolonged neutropenia resulting from both the disease and chemotherapy, along with t...

Nanorobotics at a crossroads: an overview of design, propulsion, and applications.

Nanobots are small nanoscale devices designed to perform highly specific tasks in precisely targeted areas, representing a promising approach in the d...

Development and validation of a radiomics-dosiomics model for predicting radiotherapy response in locally advanced, unresectable non-small cell lung cancer: a multi-center study.

Early assessment of treatment response is essential for optimizing cancer management, as it allows timely interventions during the course of therapy, ...

Oncotype DX: Clinical Utility, Evidence, and Future Trends in Personalized Breast Cancer Management.

The Oncotype DX assay has revolutionized the management of early-stage, hormone receptor-positive, HER2-negative breast cancer. Developed in 2004, it ...

An exploratory multimodal pipeline for recurrence prediction in CRC with XELOX therapy.

Colorectal cancer(CRC) recurrence remains a challenge despite curative surgery and adjuvant therapy. Integrating clinicopathological and liquid biopsy...

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal ovarian cancer subtype, responsible for ~ 70% of ovarian cancer-related deaths...

Deep learning applications in cancer treatment Prediction: Comprehensive research foundation for systematic review and Meta-Analysis.

Deep learning has rapidly emerged as a transformative technology in oncology, offering new capabilities in treatment response prediction and personali...

Machine Learning-Driven Prognostic Modeling in Head and Neck Adenoid Cystic Carcinoma: A Retrospective Cohort Study.

INTRODUCTION: Adenoid cystic carcinoma (ACC) of the head and neck is a rare malignancy characterized by perineural invasion, local recurrence, and dis...

What is truly evidence-based in pterygium? An umbrella review of systematic reviews and meta-analyses.

PURPOSE: To synthesize and critically appraise evidence from systematic reviews and meta-analyses on pterygium, identifying domains with robust suppor...

Reply to the Letter to the Editor: "Artificial intelligence for post-neoadjuvant axillary prediction".

Letter to the Editor: Artificial intelligence for post-neoadjuvant axillary prediction.

Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.

BACKGROUND: Periodontitis is a chronic inflammatory disease driven by host immune dysregulation. However, the specific genetic regulatory mechanisms u...

Machine learning-driven conditional survival prediction model for atypical teratoid/rhabdoid tumor.

PURPOSE: Atypical teratoid/rhabdoid tumor (AT/RT) is a rare and highly malignant pediatric brain tumor with dismal prognosis. We aimed to characterize...

An explainable predictive machine learning model of oxaliplatin induced peripheral neuropathy based on clinical data: a retrospective single center.

BACKGROUND: Oxaliplatin (OXA) is widely used in the treatment of gastrointestinal malignancies such as colorectal cancer. However, oxaliplatin-induced...

Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors from Whole-Slide Images.

Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-deri...