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Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.

Methods of information in medicine
BACKGROUND: Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the ext...

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

Brain stimulation
BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delive...

A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF.

The international journal of cardiovascular imaging
Left ventricular ejection fraction (LVEF) is the most important parameter in the assessment of cardiac function. A machine-learning algorithm was trained to guide ultrasound-novices to acquire diagnostic echocardiography images. The artificial intell...

Artificial intelligence in in vitro fertilization: a computer decision support system for day-to-day management of ovarian stimulation during in vitro fertilization.

Fertility and sterility
OBJECTIVE: To describe a computer algorithm designed for in vitro fertilization (IVF) management and to assess the algorithm's accuracy in the day-to-day decision making during ovarian stimulation for IVF when compared to evidence-based decisions by ...

Novel lateral transfer assist robot decreases the difficulty of transfer in post-stroke hemiparesis patients: a pilot study.

Disability and rehabilitation. Assistive technology
PURPOSE: The purpose of this study was to clarify whether the novel lateral transfer assist robot facilitates easier transfers compared with a wheelchair in post-stroke hemiparesis patients.

Robotic Rehabilitation in Spinal Cord Injury: A Pilot Study on End-Effectors and Neurophysiological Outcomes.

Annals of biomedical engineering
Robot-aided gait training (RAGT) has been implemented to provide patients with spinal cord injury (SCI) with a physiological limb activation during gait, cognitive engagement, and an appropriate stimulation of peripheral receptors, which are essentia...

Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors.

Journal of gastroenterology
BACKGROUND: Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS...

User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
We studied the performance of a robotic orthosis designed to assist the paretic hand after stroke. It is wearable and fully user-controlled, serving two possible roles: as a therapeutic tool that facilitates device-mediated hand exercises to recover ...