AI Medical Compendium Journal:
Clinical hemorheology and microcirculation

Showing 1 to 4 of 4 articles

Application of an artificial intelligence for quantitative analysis of endothelial capillary beds in vitro.

Clinical hemorheology and microcirculation
BACKGROUND: The use of endothelial cell cultures has become fundamental to study angiogenesis. Recent advances in artificial intelligences (AI) offer opportunities to develop automated assessment methods in medical research, analyzing larger datasets...

Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Clinical hemorheology and microcirculation
BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

Deep learning-based differentiation of peripheral high-flow and low-flow vascular malformations in T2-weighted short tau inversion recovery MRI.

Clinical hemorheology and microcirculation
BACKGROUND: Differentiation of high-flow from low-flow vascular malformations (VMs) is crucial for therapeutic management of this orphan disease.

Deep learning radiomics of ultrasonography for differentiating sclerosing adenosis from breast cancer.

Clinical hemorheology and microcirculation
OBJECTIVES: The purpose of our study is to present a method combining radiomics with deep learning and clinical data for improved differential diagnosis of sclerosing adenosis (SA)and breast cancer (BC).