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Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study

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Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study

Summary

Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study is a scholarly article[1].

Key Facts

  • Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study. Retrieved May 24, 2026, from https://4ort.xyz/entity/development-of-machine-learning-support-for-reading-whole-body-diffusion-weighted-mri-wb-mri-in-myeloma-for-the-detectio
MLA “Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/development-of-machine-learning-support-for-reading-whole-body-diffusion-weighted-mri-wb-mri-in-myeloma-for-the-detectio.
BibTeX @misc{4ortxyz_development-of-machine-learning-support-for-reading-whole-body-diffusion-weighted-mri-wb-mri-in-myeloma-for-the-detectio_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study}}, year = {2026}, url = {https://4ort.xyz/entity/development-of-machine-learning-support-for-reading-whole-body-diffusion-weighted-mri-wb-mri-in-myeloma-for-the-detectio}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study — https://4ort.xyz/entity/development-of-machine-learning-support-for-reading-whole-body-diffusion-weighted-mri-wb-mri-in-myeloma-for-the-detectio (retrieved 2026-05-24)

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