Chemotherapy

Optimization of Ethanol Extraction Conditions From Sun-Dried Apricot and Prediction of Antioxidant, Phenolic, and Flavonoid Contents and Their Effects on HCT116 Cells Using Artificial Neural Networks.

This study aimed to optimize the ethanol extraction conditions of sun-dried apricot ( L.) and evalua...

Optimizing breast cancer therapy: chemoressitance and machine learning for precision prediction.

BACKGROUND: Validate a novel in vitro resistance platform for breast cancer (BC) by assessing resist...

Immunoscore: redefining the landscape of colorectal cancer control and care.

The Immunoscore (IS), introduced by Jerome Galon in the early 2000s, evaluates immune cell densities...

Predicting clozapine-induced adverse drug reaction biomarkers using machine learning.

Clozapine is an atypical antipsychotic used for patients with treatment-resistant schizophrenia. Thi...

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor hete...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the stan...

AI-powered prediction model for neoadjuvant chemotherapy efficacy: comprehensive analysis of breast cancer histological images.

Breast cancer patients exhibit variable responses to neoadjuvant therapy (NAT), necessitating robust...

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 c...

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 ...

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 imagin...

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 s...

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 advanc...

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 ...

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) respons...

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 lar...

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...

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 ad...

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 colorect...

Corrigendum to 'CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy' [Acad Radiol 32/6 (2025) 3397-3409].

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 ...

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 colorecta...