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@Marktechpost 1 year ago
A Research Group from Stanford Studied the Possible Fine-Tuning Techniques to Generalize Latent Diffusion Models for Medical Imaging Domains Quick Read: https://www.marktechpost.com/2023/03/30/a-research-group-from-stanford-studied-the-possible-fine-tuning-techniques-to-generalize-latent-diffusion-models-for-medical-imaging-domains/ Paper: https://arxiv.org/pdf/2210.04133.pdf #ArtificialIntelligence #MachineLearning
@FelipeKitamura 3 years ago
1/20ish Do you train #MachineLearning models on #medicalimaging #data? These are a few tips to help prepare your data. A #tweetorial for #radres, #rads and #DataScientists. Inspired by a recent paper in @radiology_rsna https://pubs.rsna.org/doi/pdf/10.1148/radiol.2020192224
@AmineKorchiMD 4 years ago
✍️Automatic annotation of medical images is the holy grail of #AI in #Radiology. This paper describes #MachineLearning models to generate annotations for review & appeared to expedite annotation with high sensitivity at the expense of specificity. https://link.springer.com/article/10.1007/s10278-019-00299-9?wt_mc=alerts.TOCjournals&utm_source=toc&utm_medium=email&utm_campaign=toc_10278_33_2