AIMC Topic: United States

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Refinement of the clinical variant interpretation framework by statistical evidence and machine learning.

Med (New York, N.Y.)
BACKGROUND: Although the American College of Medical Genetics andĀ Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-bas...

Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) cine displacement encoding with stimulated echoes (DENSE) measures heart motion by encoding myocardial displacement into the signal phase, facilitating high accuracy and reproducibility of global an...

Development of machine learning model algorithm for prediction of 5-year soft tissue myxoid liposarcoma survival.

Journal of surgical oncology
BACKGROUND: Predicting survival in myxoid liposarcoma (MLS) patients is very challenging given its propensity to metastasize and the controversial role of adjuvant therapy. The purpose of this study was to develop a machine-learning algorithm for the...

A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network.

eLife
Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data...

A machine learning approach to identify distinct subgroups of veterans at risk for hospitalization or death using administrative and electronic health record data.

PloS one
BACKGROUND: Identifying individuals at risk for future hospitalization or death has been a major priority of population health management strategies. High-risk individuals are a heterogeneous group, and existing studies describing heterogeneity in hi...

Comparative study using inverse ontology cogency and alternatives for concept recognition in the annotated National Library of Medicine database.

Neural networks : the official journal of the International Neural Network Society
This paper introduces inverse ontology cogency, a concept recognition process and distance function that is biologically-inspired and competitive with alternative methods. The paper introduces inverse ontology cogency as a new alternative method. It ...

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

Biological psychiatry. Cognitive neuroscience and neuroimaging
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiology, and dermatology. However, the use of AI in mental health care and neurobiological research has been modest. Given the high morbidity and mortalit...