Chemotherapy

Chinese acupoint therapies in cancer pain management: research advances and future perspectives.

Cancer pain management (CPM) is crucial in oncology care, with current approaches including pharmacotherapy, radiotherapy, chemotherapy, nerve blocks, and psychological support. However, long-term drug use risks adverse effects and addiction, while physiotherapies often lack sustained efficacy. Therefore, identifying safer adjuvant analgesic therapies has become an urgent issue. Traditional Chines...

Non-Invasive Tumor Budding Evaluation and Correlation with Treatment Response in Bladder Cancer: A Multi-Center Cohort Study.

The clinical benefits of neoadjuvant chemoimmunotherapy (NACI) are demonstrated in patients with bladder cancer (BCa); however, more than half fail to achieve a pathological complete response (pCR). This study utilizes multi-center cohorts of 2322 patients with pathologically diagnosed BCa, collected between January 1, 2014, and December 31, 2023, to explore the correlation between tumor budding (...

Drug-Drug interactions and special considerations in breast cancer patients treated with CDK4/6 inhibitors: A comprehensive review.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have reshaped the treatment paradigm of hormone receptor positive (HR + )/HER2-negative breast cancer...

AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning.

Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resistance in cancer treatment. Given the high costs and ...

Machine Learning Model to Guide Empirical Antimicrobial Therapy in Febrile Neutropenic Patients With Hematologic Malignancies.

BACKGROUND/AIM: Optimal antimicrobial selection for patients with febrile neutropenia (FN) may differ depending on the underlying mechanisms. We aimed...

MRI-based multimodal AI model enables prediction of recurrence risk and adjuvant therapy in breast cancer.

Timely intervention and improved prognosis for breast cancer patients rely on early metastasis risk detection and accurate treatment predictions. This...

Molecular glue meets antibody: next-generation antibody-drug conjugates.

Antibody-drug conjugates (ADCs) have revolutionized oncology by enabling the delivery of cytotoxic agents. However, persistent limitations in payload ...

Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades,...

Developing hybrid mechanistic and data-driven personalized prediction models for platelet dynamics

Hematotoxicity, drug-induced damage to the blood-forming system, is a frequent side effect of cytotoxic chemotherapy and poses a significant challen...

[Integrated diagnosis and treatment of peritoneal metastasis in gastric cancer].

The high incidence and mortality rates of gastric cancer pose a significant burden on human health and public health systems. Peritoneal metastasis is...

Clinical prediction of pathological complete response in breast cancer: a machine learning study.

BACKGROUND: This study aimed to develop and validate machine learning models to predict pathological complete response (pCR) after neoadjuvant therapy...

Predicting Neo-Adjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images

Triple-negative breast cancer (TNBC) is an aggressive subtype defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human e...

Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on the Chemical Structure.

Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN...

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer.

PURPOSE: Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. C...

Machine Learning Models Predicting Hospital Admissions During Chemotherapy Utilising Longitudinal Symptom Severity Reports and Patient-Reported Outcome Measures.

Chemotherapy toxicity can lead to acute hospital admissions, negatively impacting the healthcare system and patients' well-being. Machine learning (ML...

Artificial intelligence as a predictive tool for gastric cancer: Bridging innovation, clinical translation, and ethical considerations.

With gastric cancer ranking among the most prevalent and deadly malignancies worldwide, early detection and individualized prognosis remain essential ...

Longitudinal changes in body composition during palliative systemic chemotherapy and survival outcomes in metastatic colorectal cancer.

BACKGROUND: In patients with metastatic colorectal cancer, chemotherapy may lead to changes in body composition, including skeletal muscle quantity an...

Deep learning MRI-based radiomic models for predicting recurrence in locally advanced nasopharyngeal carcinoma after neoadjuvant chemoradiotherapy: a multi-center study.

Local recurrence and distant metastasis were a common manifestation of locoregionally advanced nasopharyngeal carcinoma (LA-NPC) after neoadjuvant che...

Integrating Bulk and Single-Cell Transcriptomics with Machine Learning Reveals a Heme Metabolism-Based Panel for Lung Adenocarcinoma Chemotherapy Resistance.

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treat...

Elucidating the Prognostic and Therapeutic Implications of Insulin Resistance Genes in Breast Cancer: A Machine Learning-Powered Analysis.

Breast cancer (BC) is among the most prevalent malignancies and remains the leading cause of cancer-related mortality in women worldwide. While prior ...