Artificial Intelligence Improves the Accuracy in Histologic Classification of Breast Lesions.

Objectives: This study evaluated the usefulness of artificial intelligence (AI) algorithms as tools in improving the accuracy of histologic classification of breast tissue.

Methods: Overall, 100 microscopic photographs (test A) and 152 regions of interest in whole-slide images (test B) of breast tissue were classified into 4 classes: normal, benign, carcinoma in situ (CIS), and invasive carcinoma. The accuracy of 4 pathologists and 3 pathology residents were evaluated without and with the assistance of algorithms.

Infantile Cortical Hyperostosis: Report of a Case with Observations on Clinical Manifestations, Radiology, and Pathology with a Late Follow-Up of Eight Years.

. The purpose of our study was to investigate clinical manifestations, roentgen images, histopathological studies, and evolution of the disease in patient displaying infantile cortical hyperostosis. .

Liposclerosing myxofibrous tumor: A series of 9 cases and review of the literature.

Background: Liposclerosing myxofibrous primary bone tumor is a rare benign bone lesion that was characterized by complex mixture of various histological elements.

Methods: We have studied the radiological, clinical and pathological features of nine patients with this disorder. Pain and limping were the main symptoms.