Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1 to 10 of 210,187 articles

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Embracing artificial intelligence in surgical training: a clinical leadership perspective.

BMJ leader Jul 10, 2026
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Clinical-Radiomics Model Based on T2-Weighted and Diffusion-Weighted Magnetic Resonance Images on Predicting "Double Gray Zone" Prostate Cancer of PSA and PI-RADS.

Academic radiology Jul 10, 2026
OBJECTIVES: This study aimed to develop a clinical-radiomics model based on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) to improve the diagnostic performance in the "double gray zone" population characterized by prostate-specific ... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

European radiology Jul 11, 2026
OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model risk stratification. However, it is based on limited imaging features, which may limit diagnostic accur... read more 
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