A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images.

Importance: Breast cancer screening is among the most common radiological tasks, with more than 39 million examinations performed each year. While it has been among the most studied medical imaging applications of artificial intelligence, the development and evaluation of algorithms are hindered by the lack of well-annotated, large-scale publicly available data sets.

Objectives: To curate, annotate, and make publicly available a large-scale data set of digital breast tomosynthesis (DBT) images to facilitate the development and evaluation of artificial intelligence algorithms for breast cancer screening; to develop a baseline deep learning model for breast cancer detection; and to test this model using the data set to serve as a baseline for future research.

A generative adversarial network-based abnormality detection using only normal images for model training with application to digital breast tomosynthesis.

Deep learning has shown tremendous potential in the task of object detection in images. However, a common challenge with this task is when only a limited number of images containing the object of interest are available. This is a particular issue in cancer screening, such as digital breast tomosynthesis (DBT), where less than 1% of cases contain cancer.

Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists.

Unlabelled: A fully-automated deep learning algorithm matched performance of radiologists in assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence grading system.

Purpose: To develop an automated deep learning-based algorithm that jointly uses Posterior-Anterior (PA) and Lateral (LAT) views of knee radiographs to assess knee osteoarthritis severity according to the Kellgren-Lawrence grading system.

Materials And Methods: We used a dataset of 9739 exams from 2802 patients from Multicenter Osteoarthritis Study (MOST).

[Contemporary view on physician-patient relationship].

One of the most important conditions of successful treatment is adequate psychological contact between physician and patient. Culture of communicatio appearance of a physician, method of examination should not cause a negative reaction in patient. Contact between physician and patient may cause in patient fear or nervousness.