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Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Clinical & experimental ophthalmology
IMPORTANCE: Diagnosis codes are inadequate for accurately identifying herpes zoster (HZ) ophthalmicus (HZO). There is significant lack of population-based studies on HZO due to the high expense of manual review of medical records.

Health Care Robotics: Qualitative Exploration of Key Challenges and Future Directions.

Journal of medical Internet research
BACKGROUND: The emergence of robotics is transforming industries around the world. Robot technologies are evolving exponentially, particularly as they converge with other functionalities such as artificial intelligence to learn from their environment...

The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Journal of neuroengineering and rehabilitation
Despite upper extremity function playing a crucial role in maintaining one's independence in activities of daily living, upper extremity impairments remain one of the most prevalent post-stroke deficits. To enhance the upper extremity motor recovery ...

Presentation and diagnosis of patients with type 3 von Willebrand disease in resources-limited laboratory.

Hematology/oncology and stem cell therapy
Von Willebrand disease (VWD) is a bleeding disorder that results from decreased von Willebrand factor (VWF) activity <0.30 iu/mL. Therefore, the diagnosis of type 3 VWD in patients with bleeding requires finding a VWF:Ag and/or VWF:platelet ristoceti...

Comparison of Data Preprocessing Approaches for Applying Deep Learning to Human Activity Recognition in the Context of Industry 4.0.

Sensors (Basel, Switzerland)
According to the Industry 4.0 paradigm, all objects in a factory, including people, are equipped with communication capabilities and integrated into cyber-physical systems (CPS). Human activity recognition (HAR) based on wearable sensors provides a m...

Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Psychological methods
Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended numerical rating scales. However, when asking people about their state of mind in a natural context ...

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer.

IEEE transactions on nanobioscience
This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 b...

Pump Speed Optimization in Patients Implanted With the HeartMate 3 Device.

Transplantation proceedings
BACKGROUND: Pump speed optimization in patients implanted with a ventricular assist device represents a major challenge during the follow-up period. We present our findings on whether combined invasive hemodynamic ramp tests and cardiopulmonary exerc...

Long-term Glomerular Filtration Rate and Kidney Disease: Improving Global Outcomes Stage Stability After Conversion to Once-Daily Tacrolimus in Kidney Transplant Recipients.

Transplantation proceedings
Close monitoring of estimated glomerular filtration rate (eGFR) is important for early recognition of worsening renal function to prevent further deterioration. Safe conversion from twice-daily tacrolimus (TD-Tac) to once-daily tacrolimus (OD-Tac) ha...