AIMC Topic: Workflow
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A robust deep learning workflow to predict CD8 + T-cell epitopes.
Genome medicine
Sep 13, 2023
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)
Sep 5, 2023
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
Sep 5, 2023
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
Aug 31, 2023
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
Aug 25, 2023
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...
Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study.
Journal of medical Internet research
Aug 22, 2023
BACKGROUND: Large language model (LLM)-based artificial intelligence chatbots direct the power of large training data sets toward successive, related tasks as opposed to single-ask tasks, for which artificial intelligence already achieves impressive ...
FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines.
SLAS discovery : advancing life sciences R & D
Aug 11, 2023
The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potent...
Explanations as a New Metric for Feature Selection: A Systematic Approach.
IEEE journal of biomedical and health informatics
Aug 7, 2023
With the extensive use of Machine Learning (ML) in the biomedical field, there was an increasing need for Explainable Artificial Intelligence (XAI) to improve transparency and reveal complex hidden relationships between variables for medical practiti...
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians.
Nature medicine
Jul 17, 2023
Predictive artificial intelligence (AI) systems based on deep learning have been shown to achieve expert-level identification of diseases in multiple medical imaging settings, but can make errors in cases accurately diagnosed by clinicians and vice v...
Cross-Check QA: A Quality Assurance Workflow to Prevent Missed Diagnoses by Alerting Inadvertent Discordance Between the Radiologist and Artificial Intelligence in the Interpretation of High-Acuity CT Scans.
Journal of the American College of Radiology : JACR
Jul 8, 2023
PURPOSE: The aim of this study was to implement and evaluate a quality assurance (QA) workflow that leverages natural language processing to rapidly resolve inadvertent discordance between radiologists and an artificial intelligence (AI) decision sup...
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