Latest AI and machine learning research in state required cme for healthcare professionals.
The use of medical data for machine learning, including unsupervised methods such as clustering, is often restricted by privacy regulations such as the Health Insurance Portability and Accountability Act (HIPAA). Medical data is sensitive and highly regulated and anonymization is often insufficient to protect a patient's identity. Traditional clustering algorithms are also unsuitable for longitudi...
Canola meal, a by-product of canola oil processing, is a source of bioactive compounds that show antioxidant and skin anti-aging effects through upcycling (i.e., creative reuse). Here we describe the antioxidant and skin anti-aging effects of canola meal extract (CME) obtained by upcycling canola meal. The antioxidant capacity of CME is due in part to its antioxidative phenolics. Seven phenolics, ...
PURPOSE: Complete mesocolic excision (CME) has been associated with improved oncological outcomes in treatment of colon cancer. However, widespread ad...
We propose a novel unified frameork for automated distributed active learning (AutoDAL) to address multiple challenging problems in active learning su...
BACKGROUND: Each year, millions of Americans receive evidence-based psychotherapies (EBPs) like cognitive behavioral therapy (CBT) for the treatment o...
BACKGROUND: Complete mesocolic excision (CME) surgery is increasingly implemented for the resection of right-sided colonic cancer, possibly resulting ...
Complete mesocolic excision (CME) in right-sided colon cancers appears to confer oncological benefits compared to conventional colectomy. Identificati...
The field of artificial intelligence (AI) in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. The Ameri...
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuat...
 The objective of the study was to review the obstetric outcomes of complete hydatidiform molar pregnancies with a coexisting fetus (CHMCF), a rare c...
With vast interest in machine learning applications, more investigators are proposing to assemble large datasets for machine learning applications. We...
BACKGROUND: High-resolution medical images that include facial regions can be used to recognize the subject's face when reconstructing 3-dimensional (...
To explore the feasibility of an automatic machine-learning algorithm-based quality control system for the practice of diagnostic radiography, perform...
OBJECTIVE: To summarize our initial experience with robot-assisted complete mesocolic excision (R-CME) using a domestically produced Chinese surgical ...
Coulomb matrix eigenvalues (CMEs) are global 3D representations of molecular structure, which have been previously used to predict atomization energie...
Background Radiofrequency ultrasound data from the liver contain rich information about liver microstructure and composition. Deep learning might expl...
BACKGROUND: In this age of big data, certain models require very large data stores in order to be informative and accurate. In many cases however, the...
This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow rese...
Purpose To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial int...