AIMC Topic: Machine Learning

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Principles of artificial intelligence and its application in cardiovascular medicine.

Clinical cardiology
Artificial intelligence (AI) represents a rapidly developing field. Its use can improve diagnosis and therapy in many areas of medicine. Despite this enormous progress, many physicians perceive it as a black box and are skeptical about it. This revie...

Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing.

Cytotherapy
BACKGROUND AIMS: Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, ther...

Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces.

Journal of chemical information and modeling
In computational surface catalysis, the calculation of activation energies of chemical reactions is expensive, which, in many cases, limits our ability to understand complex reaction networks. Here, we present a universal, machine learning-based appr...

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Physics in medicine and biology
. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT v...

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

Frontiers in endocrinology
INTRODUCTION: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in...

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...

Radiomics in Carotid Plaque: A Systematic Review and Radiomics Quality Score Assessment.

Ultrasound in medicine & biology
Imaging modalities provide information on plaque morphology and vulnerability; however, they are operator dependent and miss a great deal of microscopic information. Recently, many radiomics models for carotid plaque that identify unstable plaques an...

Mean-field neural networks: Learning mappings on Wasserstein space.

Neural networks : the official journal of the International Neural Network Society
We study the machine learning task for models with operators mapping between the Wasserstein space of probability measures and a space of functions, like e.g. in mean-field games/control problems. Two classes of neural networks based on bin density a...

Artificial Intelligence and liver: Opportunities and barriers.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Artificial Intelligence (AI) has recently been shown as an excellent tool for the study of the liver; however, many obstacles still have to be overcome for the digitalization of real-world hepatology. The authors present an overview of the current st...

Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining method.

Scientific reports
Severe asthma is a chronic inflammatory airway disease with great therapeutic challenges. Understanding the genetic and molecular mechanisms of severe asthma may help identify therapeutic strategies for this complex condition. RNA expression data wer...