Detecting MRI-Invisible Prostate Cancers Using a Weakly Supervised Deep Learning Model
CONCLUSIONS: In conclusion, the proposed WSUNet could effectively detect MIPCas, thereby reducing unnecessary biopsies.PMID:38532840 | PMC:PMC10965281 | DOI:10.1155/2024/2741986 (Source: International Journal of Biomedical Imaging)
Source: International Journal of Biomedical Imaging - March 27, 2024 Category: Radiology Authors: Yao Zheng Jingliang Zhang Dong Huang Xiaoshuo Hao Weijun Qin Yang Liu Source Type: research

Empowering Radiographers: A Call for Integrated AI Training in University Curricula
CONCLUSIONS: This study suggests that medical practices have a favorable attitude towards AI in the radiology field. Most participants surveyed believed that AI should be part of radiography education. AI training programs for undergraduate and postgraduate radiographers may be necessary to prepare them for AI tools in radiology development.PMID:38496776 | PMC:PMC10942819 | DOI:10.1155/2024/7001343 (Source: International Journal of Biomedical Imaging)
Source: International Journal of Biomedical Imaging - March 18, 2024 Category: Radiology Authors: Mohammad A Rawashdeh Sara Almazrouei Maha Zaitoun Praveen Kumar Charbel Saade Source Type: research