AI Medical Compendium Topic

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Transformer-based tool recommendation system in Galaxy.

BMC bioinformatics
BACKGROUND: Galaxy is a web-based open-source platform for scientific analyses. Researchers use thousands of high-quality tools and workflows for their respective analyses in Galaxy. Tool recommender system predicts a collection of tools that can be ...

Toward a deep learning-based magnetic resonance imaging only workflow for postimplant dosimetry in I-125 seed brachytherapy for prostate cancer.

Brachytherapy
BACKGROUND AND PURPOSE: The current standard imaging-technique for creating postplans in seed prostate brachytherapy is computed tomography (CT), that is associated with additional radiation exposure and poor soft tissue contrast. To establish a magn...

Practical Applications of Artificial Intelligence in Spine Imaging: A Review.

Radiologic clinics of North America
Artificial intelligence (AI), a transformative technology with unprecedented potential in medical imaging, can be applied to various spinal pathologies. AI-based approaches may improve imaging efficiency, diagnostic accuracy, and interpretation, whic...

Deep Learning in Surgical Workflow Analysis: A Review of Phase and Step Recognition.

IEEE journal of biomedical and health informatics
OBJECTIVE: In the last two decades, there has been a growing interest in exploring surgical procedures with statistical models to analyze operations at different semantic levels. This information is necessary for developing context-aware intelligent ...

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images.

Physics in medicine and biology
Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still...

Workflow for Evaluating Normalization Tools for Omics Data Using Supervised and Unsupervised Machine Learning.

Journal of the American Society for Mass Spectrometry
To achieve high quality omics results, systematic variability in mass spectrometry (MS) data must be adequately addressed. Effective data normalization is essential for minimizing this variability. The abundance of approaches and the data-dependent n...

Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

The international journal of cardiovascular imaging
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recentl...

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 ...