AIMC Topic: Artificial Intelligence

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A primer on artificial intelligence in pancreatic imaging.

Diagnostic and interventional imaging
Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered s...

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function.

Seminars in ultrasound, CT, and MR
The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to...

Artificial intelligence in molecular de novo design: Integration with experiment.

Current opinion in structural biology
In this mini review, we capture the latest progress of applying artificial intelligence (AI) techniques based on deep learning architectures to molecular de novo design with a focus on integration with experimental validation. We will cover the progr...

Evaluating Synthetic Medical Images Using Artificial Intelligence with the GAN Algorithm.

Sensors (Basel, Switzerland)
In recent years, considerable work has been conducted on the development of synthetic medical images, but there are no satisfactory methods for evaluating their medical suitability. Existing methods mainly evaluate the quality of noise in the images,...

Human-Centered Design to Address Biases in Artificial Intelligence.

Journal of medical Internet research
The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner. This perspective identifies potential biases in each stag...

Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.

Clinical oral implants research
OBJECTIVES: To develop and assess the performance of a novel artificial intelligence (AI)-driven convolutional neural network (CNN)-based tool for automated three-dimensional (3D) maxillary alveolar bone segmentation on cone-beam computed tomography ...