Cardiovascular

Weakly supervised multi-modal contrastive learning framework for predicting the HER2 scores in breast cancer.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and prediction of treatment response in breast cancer (BC). HER2 scoring is typically evaluated by pathologist microscopic observation on immunohistochemistry (IHC) images, which is labor-intensive and results in observational biases among different pathologists. Most existing methods generally use hand-crafted...

A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things.

With bio-medical wearables becoming an essential part of Internet of Medical things (IoMT) for monitoring the health of workers, patients and others in different environments, antenna play a pivotal role in such wearables. In this communication, a novel Horse shoe shaped antenna (HSPA) meant for such wearables is presented. The vitals of the workers, patients etc. are collected and sent to the IoM...

Hybrid transformer-based model for mammogram classification by integrating prior and current images.

BACKGROUND: Breast cancer screening via mammography plays a crucial role in early detection, significantly impacting women's health outcomes worldwide...

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiom...

Machine learning models for water safety enhancement.

Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial radionuclides, and radiation generated by human acti...

F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

PURPOSE: Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer...

Exploring the Social Media Discussion of Breast Cancer Treatment Choices: Quantitative Natural Language Processing Study.

BACKGROUND: Early-stage breast cancer has the complex challenge of carrying a favorable prognosis with multiple treatment options, including breast-co...

Machine learning-based lactate-related genes signature predicts clinical outcomes and unveils novel therapeutic targets in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC), a predominant subtype of esophageal cancer, typically presents with poor prognosis. Lactate is a crucial me...

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of p...

Non-invasive Assessment of Human Epidermal Growth Factor Receptor 2 Expression in Gastric Cancer Based on Deep Learning: A Computed Tomography-based Multicenter Study.

RATIONALE AND OBJECTIVES: The expression of human epidermal growth factor receptor 2 (HER2) in gastric cancer is closely associated with its treatment...

Feature-targeted deep learning framework for pulmonary tumorous Cone-beam CT (CBCT) enhancement with multi-task customized perceptual loss and feature-guided CycleGAN.

Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation therapy (IGRT) to provide updated patient anatomy i...

Unrolled deep learning for breast cancer detection using limited-view photoacoustic tomography data.

Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detection, offering unique advantages in visualizing tiss...

Semiautomated Extraction of Research Topics and Trends From National Cancer Institute Funding in Radiological Sciences From 2000 to 2020.

PURPOSE: Investigators and funding organizations desire knowledge on topics and trends in publicly funded research but current efforts for manual cate...

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcin...

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy asses...

Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.

BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, th...

A deep learning approach for early prediction of breast cancer neoadjuvant chemotherapy response on multistage bimodal ultrasound images.

Neoadjuvant chemotherapy (NAC) is a systemic and systematic chemotherapy regimen for breast cancer patients before surgery. However, NAC is not effect...

Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions.

This white paper examines the potential of pioneering technologies and artificial intelligence-driven solutions in advancing clinical trials involving...

Predicting Postoperative Infection After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy with Splenectomy.

BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of inf...

Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with...