AIMC Topic: Artificial Intelligence

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Foresight science in conservation: Tools, barriers, and mainstreaming opportunities.

Ambio
Foresight science is a systematic approach to generate future predictions for planning and management by drawing upon analytical and predictive tools to understand the past and present, while providing insights about the future. To illustrate the app...

Artificial intelligence in intensive care: moving towards clinical decision support systems.

Minerva anestesiologica
The high complexity of care in the Intensive Care Unit environment has led, in the last decades, to a big effort in term of the improvement of patient's monitoring devices, increase of diagnostic and therapeutic opportunities, and development of elec...

Artificial Intelligence and Deep Learning for Rheumatologists.

Arthritis & rheumatology (Hoboken, N.J.)
Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications across medicine. Deep learning could have particular relevance to rheumatology if correctly utilize...

AI4VIS: Survey on Artificial Intelligence Approaches for Data Visualization.

IEEE transactions on visualization and computer graphics
Visualizations themselves have become a data format. Akin to other data formats such as text and images, visualizations are increasingly created, stored, shared, and (re-)used with artificial intelligence (AI) techniques. In this survey, we probe the...

Addressing Noise and Estimating Uncertainty in Biomedical Data through the Exploration of Chemical Space.

International journal of molecular sciences
Noise is a basic ingredient in data, since observed data are always contaminated by unwanted deviations, i.e., noise, which, in the case of overdetermined systems (with more data than model parameters), cause the corresponding linear system of equati...

Understanding basic principles of Artificial Intelligence: a practical guide for intensivists.

Acta bio-medica : Atenei Parmensis
BACKGROUND AND AIM: Artificial intelligence was born to allow computers to learn and control their environment, trying to imitate the human brain structure by simulating its biological evolution. Artificial intelligence makes it possible to analyze l...

Artificial intelligence-based methods for fusion of electronic health records and imaging data.

Scientific reports
Healthcare data are inherently multimodal, including electronic health records (EHR), medical images, and multi-omics data. Combining these multimodal data sources contributes to a better understanding of human health and provides optimal personalize...

Virtual Biopsy by Using Artificial Intelligence-based Multimodal Modeling of Binational Mammography Data.

Radiology
Background Computational models based on artificial intelligence (AI) are increasingly used to diagnose malignant breast lesions. However, assessment from radiologic images of the specific pathologic lesion subtypes, as detailed in the results of bio...

Current understanding of biological interactions and processing of DNA origami nanostructures: Role of machine learning and implications in drug delivery.

Biotechnology advances
DNA origami has emerged as an exciting avenue that provides a versatile two and three-dimensional DNA-based platform for nanomedicine and drug delivery applications. Their incredible programmability, custom synthesis, efficiency, biocompatibility, an...