Chemotherapy

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...

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...

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. How...

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 tum...

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 ...

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 ...

Development and validation of pathomics signature for predicting prognosis of advanced high-grade serous ovarian carcinoma patients after platinum-based chemotherapy.

In patients with advanced high-grade serous ovarian carcinoma (HGSOC), the standard treatment typica...

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment ...

Predicting Treatment Response After Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer.

OBJECTIVE: To develop a predictive model for pathological complete response (pCR) after total neoadj...

Development and validation of an interpretable machine learning model for predicting postoperative complications after transanal total mesorectal excision: a multicenter study.

OBJECTIVE: This study aimed to develop and externally validate an interpretable machine learning (ML...

Atopic dermatitis.

Atopic dermatitis (AD) is the most common inflammatory skin disease and carries the highest disabili...

Artificial intelligence in predicting anesthetic complications: current techniques, clinical applications, and limitations.

Artificial intelligence (AI) is revolutionizing anesthesiology by enhancing the prediction and manag...

Multi-omic biomarkers of neoadjuvant treatment response in rectal cancer: A narrative review.

BACKGROUND: Neoadjuvant treatment response in rectal cancer is highly heterogeneous, complicating pa...

CeO2 Nanozymes as redox regulators: Reprogramming of reactive oxygen species (ROS) signaling for plant climate resilience.

Climate change-induced abiotic stress, including heat, cold, salinity, and drought, increasingly thr...

Cytotoxicity mitigation in drinking water upon chlorination: Enhancing aged biological activated carbon filters with micro- and nanobubbles.

It has been demonstrated that the cytotoxicity reduction of chlorinated water by aged biological act...

A Foundation Model Based CT Biomarker for Non-Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non-Small Cell Lung Cancer.

Predicting pathological complete response (pCR) to neoadjuvant immunochemotherapy in non-small cell ...

Machine learning-based identification of high-risk triple-negative breast cancer patients despite pathological complete response after neoadjuvant chemotherapy.

The binary pathological complete response (pCR) status of triple-negative breast cancer (TNBC) patie...

Deep learning prediction of pathological complete response in breast cancer using Mamba architecture.

Deep learning is capable of efficiently predicting the therapeutic efficacy of neoadjuvant chemother...

Perihilar Cholangiocarcinoma in Primary Sclerosing Cholangitis.

This clinical review details the current approach for the detection and management of perihilar chol...