Chemotherapy

Deciphering aging-associated prognosis and heterogeneity in gastric cancer through a machine learning-driven approach.

Gastric cancer (GC) is a prevalent malignancy with a high mortality rate and limited treatment optio...

Artificial-intelligence-enhanced ECG: a potential solution to limitations of ECG in detecting left ventricular dysfunction after chemotherapy.

Extract optimization and biological activities of Otidea onotica using Artificial Neural Network-Genetic Algorithm and response surface methodology techniques.

In this study, the biological activities of Otidea onotica were investigated using two optimization ...

Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries.

The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed i...

Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.

Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs)...

Enhancing prediction and stratifying risk: machine learning and bayesian-learning models for catheter-related thrombosis in chemotherapy patients.

BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoin...

Individualized Analysis of Nipple-Sparing Mastectomy Versus Modified Radical Mastectomy Using Deep Learning.

BACKGROUND: This study aimed to evaluate the impact of nipple-sparing mastectomy (NSM) and modified ...

Predicting postoperative nausea and vomiting using machine learning: a model development and validation study.

BACKGROUND: Postoperative nausea and vomiting (PONV) is a frequently observed complication in patien...

A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation.

Colorectal cancer (CRC) is a prevalent gastrointestinal tumor worldwide with high morbidity and mort...

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C ...

Multimodal diagnostic models and subtype analysis for neoadjuvant therapy in breast cancer.

BACKGROUND: Breast cancer, a heterogeneous malignancy, comprises multiple subtypes and poses a subst...

Utility of comprehensive genomic profiling combined with machine learning for prognostic stratification in stage II/III colorectal cancer after adjuvant chemotherapy.

BACKGROUND AND PURPOSE: Accurate recurrence risk evaluation in patients with stage II and III colore...

Machine learning-based prediction reveals kinase MAP4K4 regulates neutrophil differentiation through phosphorylating apoptosis-related proteins.

Neutrophils, an essential innate immune cell type with a short lifespan, rely on continuous replenis...

Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy.

BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunoth...

Unsupervised learning to identify symptom clusters in older adults undergoing chemotherapy.

INTRODUCTION: Unsupervised machine learning (ML) approaches such as clustering have not been commonl...

Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods.

RATIONALE: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast ...

Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes.

Predicting the solubility and lipophilicity of platinum(II, IV) complexes is essential for prioritiz...

Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer.

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology feature...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, a...

Prognostic model for log odds of negative lymph node in locally advanced rectal cancer via interpretable machine learning.

No studies have examined the prognostic value of the log odds of negative lymph nodes/T stage (LONT)...

Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological Cancers.

Homologous recombination deficiency (HRD) is a well-recognized important biomarker in determining th...