Risk Management

Protocol to analyze fundus images for multidimensional quality grading and real-time guidance using deep learning techniques.

Data quality issues have been acknowledged as one of the greatest obstacles in medical artificial intelligence research. Here, we present DeepFundus, which employs deep learning techniques to perform multidimensional classification of fundus image quality and provide real-time guidance for on-site image acquisition. We describe steps for data preparation, model training, model inference, model eva...

Using DeepContact with Amira graphical user interface.

DeepContact is a deep learning software for high-throughput quantification of membrane contact site (MCS) in 2D electron microscopy images. This protocol will guide users through incorporating available DeepContact models in Amira's artificial intelligence module, thereby allowing invoking of DeepContact functions in organelle segmentation and quantifying of MCS with a user-friendly graphical user...

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15.

We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were ob...

Artificial intelligence: a new editor limiting self-citation malpractice.

Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only...

A narrative review of recent tools and innovations toward automating living systematic reviews and evidence syntheses.

Living reviews are an increasingly popular research paradigm. The purpose of a 'living' approach is to allow rapid collation, appraisal and synthesis ...

Ethical Considerations of Using ChatGPT in Health Care.

ChatGPT has promising applications in health care, but potential ethical issues need to be addressed proactively to prevent harm. ChatGPT presents pot...

Streamlining Large Chemical Library Docking with Artificial Intelligence: the PyRMD2Dock Approach.

The present contribution introduces a novel computational protocol called PyRMD2Dock, which combines the Ligand-Based Virtual Screening (LBVS) tool Py...

Development and accuracy of artificial intelligence-generated prediction of facial changes in orthodontic treatment: a scoping review.

Artificial intelligence (AI) has been utilized in soft-tissue analysis and prediction in orthodontic treatment planning, although its reliability has ...

Developing and deploying deep learning models in brain magnetic resonance imaging: A review.

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and ...

Patient Perspectives on Artificial Intelligence in Radiology.

There are two major areas for patient engagement in radiology artificial intelligence (AI). One is in the sharing of data for AI development; the seco...

Protocol for automated multivariate quantitative-image-based cytometry analysis by fluorescence microscopy of asynchronous adherent cells.

Here, we present a protocol for multivariate quantitative-image-based cytometry (QIBC) analysis by fluorescence microscopy of asynchronous adherent ce...

Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction.

PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them bet...

Applications of artificial intelligence in magnetic resonance imaging of primary pediatric cancers: a scoping review and CLAIM score assessment.

PURPOSES: To review the uses of AI for magnetic resonance (MR) imaging assessment of primary pediatric cancer and identify common literature topics an...

Protocol for the automatic extraction of epidemiological information via a pre-trained language model.

The lack of systems to automatically extract epidemiological fields from open-access COVID-19 cases restricts the timeliness of formulating prevention...

Fast high-quality MRI protocol of the lumbar spine with deep learning-based algorithm: an image quality and scanning time comparison with standard protocol.

OBJECTIVE: The objective of this study is to prospectively compare quantitative and subjective image quality, scanning time, and diagnostic confidence...

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments.

Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional radiology. Starting in the early 1970s, this imaging ...

Ethical considerations on artificial intelligence in dentistry: A framework and checklist.

OBJECTIVE: Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers t...

Observer-based state estimation for discrete-time semi-Markovian jump neural networks with round-robin protocol against cyber attacks.

This paper investigates an observer-based state estimation issue for discrete-time semi-Markovian jump neural networks with Round-Robin protocol and c...

Supporting SURgery with GEriatric Co-Management and AI (SURGE-Ahead): A study protocol for the development of a digital geriatrician.

INTRODUCTION: Geriatric co-management is known to improve treatment of older adults in various clinical settings, however, widespread application of t...