Altered intrinsic cerebellar-cerebral functional connectivity is related to negative symptoms in patients with first-episode psychosis.

Background: Negative symptoms in schizophrenia include cognitive and affective dysfunction, such as diminished expression and amotivation. Although the cerebellar posterior hemisphere and vermis are involved in cognitive and affective functioning, previous studies on the neural mechanism of negative symptoms have mostly been confined to the cerebral cortex. This study aimed to investigate whether resting-state cerebellar-cerebral functional connectivity (FC) is altered in first-episode psychosis (FEP) patients and whether this connectivity is related to negative symptoms.

Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs: Case-control study.

Along with recent developments in deep learning techniques, computer-aided diagnosis (CAD) has been growing rapidly in the medical imaging field. In this work, we evaluate the deep learning-based CAD algorithm (DCAD) for detecting and localizing 3 major thoracic abnormalities visible on chest radiographs (CR) and to compare the performance of physicians with and without the assistance of the algorithm. A subset of 244 subjects (60% abnormal CRs) was evaluated.