Chemotherapy

Prognostic Utility of a Deep Learning Radiomics Nomogram Integrating Ultrasound and Multi-Sequence MRI in Triple-Negative Breast Cancer Treated With Neoadjuvant Chemotherapy.

OBJECTIVE: The aim of this study is to evaluate the prognostic performance of a nomogram integrating clinical parameters with deep learning radiomics (DLRN) features derived from ultrasound and multi-sequence magnetic resonance imaging (MRI) for predicting survival, recurrence, and metastasis in patients diagnosed with triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC)....

Novel risk calculator predicting long-term survival in pediatric versus adult patients diagnosed with spinal low-grade glioma: a nationwide analysis.

BACKGROUND CONTEXT: Spinal low-grade gliomas (SLGGs) are rare, slow-growing central nervous system tumors affecting both pediatric and adult populations. Due to their rarity, their prognosis and optimal treatment strategies remain poorly defined, necessitating further investigation into age-related differences in outcomes and risk factors. PURPOSE: This study aims to evaluate differences in treatm...

Comparative analysis of tumor and mesorectum radiomics in predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.

PURPOSE: Neoadjuvant chemoradiotherapy (CRT) is known to increase sphincter preservation rates and decrease the risk of postoperative recurrence in pa...

Crafting an innovative one health-aligned machine learning framework for neglected tropical diseases elimination.

INTRODUCTION: Strategic investment in new interventions is crucial for controlling and eliminating NTDs. However, selecting the optimal intervention c...

Diffusion-weighted imaging in rectal cancer MRI from theory to practice.

Diffusion-weighted imaging (DWI) has become a cornerstone of high-resolution rectal MRI, providing critical functional information that complements T2...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of survival outcomes based on treatment modalities, i....

Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer.

With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary stag...

Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer.

BACKGROUND: Accurate prediction of pathological complete response (pCR) to neoadjuvant chemotherapy has significant clinical utility in the management...

Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.

Purpose To improve the generalizability of pathologic complete response (pCR) prediction following neoadjuvant chemotherapy using deep learning (DL)-...

Predicting the prognosis of radical gastrectomy for patients with locally advanced gastric cancer after neoadjuvant chemotherapy using machine learning technology: a multicenter study in China.

BACKGROUND: Neoadjuvant chemotherapy (NAC) can improve the prognosis of patients with locally advanced gastric cancer (LAGC). However, precise models ...

Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical study.

PURPOSE: This study aimed to develop an early predictive model for neoadjuvant therapy (NAT) response in breast cancer by integrating multimodal ultra...

Machine learning-driven programmed cell death signature for prognosis and drug candidate discovery in diffuse large B-cell lymphoma: Multi-cohort study and experimental validation.

BACKGROUND: Relapse and drug resistance are major contributor to chemotherapy failure in diffuse large B-cell lymphoma (DLBCL). Programmed cell death ...

Metabolic alterations driven by LDHA in CD8 + T cells promote immune evasion and therapy resistance in NSCLC.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite advancements in treatment, prognosis for patients wi...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC) remains a clinically challenging subtype within ...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgic...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate survival prediction is essential for managing thes...

Machine learning models for predicting chemotherapy-induced adverse drug reactions in colorectal cancer patients.

BACKGROUND: Chemotherapy-induced adverse drug reactions (ADRs) are common in patients with colorectal cancer. We developed four machine learning model...

Predicting acute diarrhoea in rectal cancer chemoradiotherapy: Secondary analysis of the phase III ARISTOTLE trial.

BACKGROUND: Neoadjuvant chemoradiotherapy is a standard treatment for locally advanced rectal cancer, but acute diarrhoea remains a significant side e...

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor ...

Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by high morbidity and poor prognosis. The complex mo...