Cardiovascular

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) models identifying patients at risk of emergency admissions are often developed on data lacking patients' perspective. This study used longitudinally collected symptom severity reports and 4 ML models to predict hospital admissions risk during chem...

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 and quality, and body fat area and distribution. Longitudinal follow-up data in a homogeneous population are required to understand these changes better.

Prognostic value of circadian rhythm-associated genes in breast cancer.

OBJECTIVE: Breast cancer (BC) remains the most prevalent malignancy among women. Clinical evidence indicates that genetic variations related to circad...

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...

Enhancing Climate-Driven Urban Tree Cooling with Targeted Nonclimatic Interventions.

Urban trees play a pivotal role in mitigating heat, yet the global determinants and patterns of their cooling efficiency (CE) remain elusive. Here, we...

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.

Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strateg...

Evaluation of an artificial intelligence noise reduction tool for conventional X-ray imaging - a visual grading study of pediatric chest examinations at different radiation dose levels using anthropomorphic phantoms.

BACKGROUND: Noise reduction tools developed with artificial intelligence (AI) may be implemented to improve image quality and reduce radiation dose, w...

Redefining Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer in the Era of Novel Antibody-Drug Conjugates.

The advent of next-generation antibody-drug conjugates (ADCs), particularly trastuzumab deruxtecan (T-DXd), has transformed our understanding of human...

Effect of Cell-Cell Interaction on Single-Cell Behavior Revealed by a Deep Learning-Aided High-Throughput Addressable Single-Cell Coculture System.

Cell-cell interactions are crucial for understanding various physiological and pathological processes, yet conventional population-level methods fail ...

Unraveling the molecular mechanisms of paclitaxel in high-grade serous ovarian cancer through network pharmacology.

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of epithelial ovarian cancer, often diagnosed at advanced stages wi...

Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on F-FDG PET/CT radiomics.

PURPOSE: According to the updated classification system, human epidermal growth factor receptor 2 (HER2) expression statuses are divided into the foll...

Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) is a novel predictive biomarker for chemotherapy and immunotherapy response, as well as prognostic indicat...

Emerging biomarkers for pancreatic cancer: from early detection to personalized therapy.

Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its poor prognosis and late diagnosis. Biomarkers are essential i...

CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinoma

Causal machine learning (CML) enables individualized estimation of treatment effects, offering critical advantages over traditional correlation-base...

Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising

Breast cancer is the most frequently diagnosed human cancer in the United States at present. Early detection is crucial for its successful treatment...

Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.

While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic an...

Evaluating the Effectiveness of Geant4 Software in Measuring the Damage Caused by Ti48 Ion Radiation on Nerve Cells, in Comparison to the Biophysical Model and Empirical Data.

INTRODUCTION: Presently, heavy particle ion radiation therapy is commonly utilized for the treatment of deep-seated malignancies, such as brain tumors...

[Urban Ozone Driving Factors Based on Explainable Machine Learning].

Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provincial control sites, and one background site, were se...

A quantitative characterization of the heterogeneous response of glioblastoma U-87 MG cell line to temozolomide.

Most cancers are genetically and phenotypically heterogeneous. This includes subpopulations of cells with different levels of sensitivity to chemother...

Deep Learning-Based Retinoblastoma Protein Subtyping of Pulmonary Large-Cell Neuroendocrine Carcinoma on Small Hematoxylin and Eosin-Stained Specimens.

Molecular subtyping of pulmonary large-cell neuroendocrine carcinoma (LCNEC) based on retinoblastoma protein (pRb) expression may influence systemic t...