AIMC Topic: Humans

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Can natural language processing models extract and classify instances of interpersonal violence in mental healthcare electronic records: an applied evaluative study.

BMJ open
OBJECTIVE: This paper evaluates the application of a natural language processing (NLP) model for extracting clinical text referring to interpersonal violence using electronic health records (EHRs) from a large mental healthcare provider.

Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records.

BMC medical informatics and decision making
PURPOSE: Predictively diagnosing infectious diseases helps in providing better treatment and enhances the prevention and control of such diseases. This study uses actual data from a hospital. A multiple infectious disease diagnostic model (MIDDM) is ...

Deep learning fetal ultrasound video model match human observers in biometric measurements.

Physics in medicine and biology
This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestati...

Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.

Journal of healthcare engineering
Glaucoma is the second most common cause for blindness around the world and the third most common in Europe and the USA. Around 78 million people are presently living with glaucoma (2020). It is expected that 111.8 million people will have glaucoma b...

Improving Automatic Control of Upper-Limb Prosthesis Wrists Using Gaze-Centered Eye Tracking and Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Many upper-limb prostheses lack proper wrist rotation functionality, leading to users performing poor compensatory strategies, leading to overuse or abandonment. In this study, we investigate the validity of creating and implementing a data-driven pr...

Compound computer vision workflow for efficient and automated immunohistochemical analysis of whole slide images.

Journal of clinical pathology
AIMS: Immunohistochemistry (IHC) assessment of tissue is a central component of the modern pathology workflow, but quantification is challenged by subjective estimates by pathologists or manual steps in semi-automated digital tools. This study integr...

An Early Prospective Clinical Study to Evaluate the Safety and Performance of the Versius Surgical System in Robot-Assisted Cholecystectomy.

Annals of surgery
OBJECTIVE: The aim of this study was to demonstrate the ability of the Versius Surgical System to successfully and safely complete cholecystectomy.

A technical guide to robotic catheter angiography with the Corindus CorPath GRX system.

Journal of neurointerventional surgery
Robotic catheter angiography is an emerging technology with the opportunity to increase procedural precision and decrease occupational hazards.1-5 In this video, we present our initial experiences with the CorPath GRX Robotic System (Corindus, a Seim...

High-order control barrier functions-based impedance control of a robotic manipulator with time-varying output constraints.

ISA transactions
This paper focuses on the impedance control for robotic manipulators with time-varying output constraints. High-order control barrier functions (HoCBFs) are firstly proposed for a nonlinear system with high relative-degree time-varying constraints. T...

Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Background parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI-RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assess...