Latest AI and machine learning research in cardiovascular for healthcare professionals.
The proliferation of toxigenic fungi in food and the subsequent production of mycotoxins constitute a significant concern in the fields of public health and consumer protection. This review highlights recent strategies and emerging methods aimed at preventing fungal growth and mycotoxin contamination in food matrices as opposed to traditional approaches such as chemical fungicides, which may leave...
PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. This study aims to enhance pre-selection of patients for testing using machine learning.
INTRODUCTION: Artificial intelligence (AI) is now transforming medical imaging, with extensive ramifications for nearly every aspect of diagnostic ima...
Contrast-Enhanced Spectral Mammography (CESM) is a dual-energy mammographic technique that improves lesion visibility through the administration of ...
Cone-beam computed tomography (CBCT) is a critical 3D imaging technology in the medical field, while the high radiation exposure required for high-q...
Unsupervised learning of disease subtypes from multi-omics data presents a significant opportunity for advancing personalized medicine. We introduce...
Surgery plays an important role within the treatment for neuroblastoma, a common pediatric cancer. This requires careful planning, often via magneti...
Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breas...
Based on observed meteorological elements, photolysis rates (J-values) and pollutant concentrations, an automated J-values predicting system by machin...
BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and MR components and radiation exposure associated w...
PURPOSE: Artificial intelligence (AI) tools could improve clinical decision making or exacerbate inequities because of bias. African American (AA) men...
Accurate detection of breast cancer from high-resolution mammograms is crucial for early diagnosis and effective treatment planning. Previous studie...
Purpose: The scarcity of high-quality curated labeled medical training data remains one of the major limitations in applying artificial intelligence...
Malignant gliomas (MGs), particularly glioblastoma, are among the most aggressive brain tumors, with limited treatment options and a poor prognosis....
Radiometers are crucial instruments in radio astronomy, forming the primary component of nearly all radio telescopes. They measure the intensity of ...
The aim is to create a method for accurately estimating the duration of post-cancer treatment, particularly focused on chemotherapy, to optimize pat...
Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication re...
PURPOSE: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate...
Artificial intelligence (AI) and the introduction of Large Language Model (LLM) chatbots have become a common source of patient inquiry in healthcare....
Efficiently acquired and precisely reconstructed imaging are crucial to the success of modern radiation therapy (RT). Computed tomography (CT) and m...