OBJECTIVES: To predict urinary continence recovery after robot-assisted radical prostatectomy (RARP) using a deep learning (DL) model, which was then used to evaluate surgeon's historical patient outcomes.
Journal of neuroengineering and rehabilitation
Mar 20, 2019
BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesi...
BACKGROUND: The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics and related fields.
PURPOSE: We aimed to use deep learning with convolutional neural network (CNN) to discriminate between benign and malignant breast mass images from ultrasound.
The Kaohsiung journal of medical sciences
Mar 19, 2019
In this study, we compared the long-term oncological and functional outcomes of laparoscopic partial nephrectomy (LPN) and robot-assisted laparoscopic partial nephrectomy (RAPN) performed in the treatment of renal tumors. The data of 142 patients (RA...
BACKGROUND: In the United States, 13% of adults are estimated to have alcohol use disorder (AUD). Most studies examining the neurobiology of AUD treat individuals with this disorder as a homogeneous group; however, the theories of the neurocircuitry ...
In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistic...
In this paper, we propose bag of adversarial features (BAFs) for identifying mild traumatic brain injury (MTBI) patients from their diffusion magnetic resonance images (MRIs) (obtained within one month of injury) by incorporating unsupervised feature...
Journal of magnetic resonance imaging : JMRI
Mar 18, 2019
BACKGROUND: FLAIR (fluid attenuated inversion recovery) imaging via synthetic MRI methods leads to artifacts in the brain, which can cause diagnostic limitations. The main sources of the artifacts are attributed to the partial volume effect and flow,...
BMC medical informatics and decision making
Mar 18, 2019
BACKGROUND: Digital health interventions can fill gaps in mental healthcare provision. However, autonomous e-mental health (AEMH) systems also present challenges for effective risk management. To balance autonomy and safety, AEMH systems need to dete...
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