AIMC Topic: Workflow

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Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows.

Scientific data
Recent advances in computer-aided diagnosis, treatment response and prognosis in radiomics and deep learning challenge radiology with requirements for world-wide methodological standards for labeling, preprocessing and image acquisition protocols. Th...

Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard.

Current problems in diagnostic radiology
Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and B...

Theoretical modeling and machine learning-based data processing workflows in comprehensive two-dimensional gas chromatography-A review.

Journal of chromatography. A
In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional ...

Improving radiology workflow using ChatGPT and artificial intelligence.

Clinical imaging
Artificial Intelligence is a branch of computer science that aims to create intelligent machines capable of performing tasks that typically require human intelligence. One of the branches of artificial intelligence is natural language processing, whi...

Multilevel effective surgical workflow recognition in robotic left lateral sectionectomy with deep learning: experimental research.

International journal of surgery (London, England)
BACKGROUND: Automated surgical workflow recognition is the foundation for computational models of medical knowledge to interpret surgical procedures. The fine-grained segmentation of the surgical process and the improvement of the accuracy of surgica...

A robust deep learning workflow to predict CD8 + T-cell epitopes.

Genome medicine
BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focus...

Comparison of four synthetic CT generators for brain and prostate MR-only workflow in radiotherapy.

Radiation oncology (London, England)
BACKGROUND: The interest in MR-only workflows is growing with the introduction of artificial intelligence in the synthetic CT generators converting MR images into CT images. The aim of this study was to evaluate several commercially available sCT gen...

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.

PLoS computational biology
Many therapies in clinical trials are based on single drug-single target relationships. To further extend this concept to multi-target approaches using multi-targeted drugs, we developed a machine learning pipeline to unravel the target landscape of ...

Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology.

AJNR. American journal of neuroradiology
In this review, concepts of algorithmic bias and fairness are defined qualitatively and mathematically. Illustrative examples are given of what can go wrong when unintended bias or unfairness in algorithmic development occurs. The importance of expla...

PIMedSeg: Progressive interactive medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate object segmentation in medical images is a crucial step in medical diagnosis and other applications. Despite years of research on automatic segmentation approaches, achieving clinically acceptable image quality rema...