AIMC Topic: Humans

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[DeRAS I-German situation of robotic-assisted surgery-an online survey].

Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
BACKGROUND: Robotic assistance has become established in surgery but is not yet a standard procedure. The current status of clinical dissemination in Germany remains unclear. Industry independent sources are scarce.

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

International journal of hematology
This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose methotrexate (HD-MTX) based on machine learning. A total of 205 patients were recruited. Five variables ...

Video recognition of simple mastoidectomy using convolutional neural networks: Detection and segmentation of surgical tools and anatomical regions.

Computer methods and programs in biomedicine
A simple mastoidectomy is used to remove inflammation of the mastoid cavity and to create a route to the skull base and middle ear. However, due to the complexity and difficulty of the simple mastoidectomy, implementing robot vision for assisted surg...

Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal ch...

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Computers in biology and medicine
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many art...

Automatic Detection and Classification of Multiple Catheters in Neonatal Radiographs with Deep Learning.

Journal of digital imaging
We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using a dataset of 777 neonatal chest and abdominal radiographs, with a spl...

Deep learning-based automated left ventricular ejection fraction assessment using 2-D echocardiography.

American journal of physiology. Heart and circulatory physiology
Deep learning (DL) has been applied for automatic left ventricle (LV) ejection fraction (EF) measurement, but the diagnostic performance was rarely evaluated for various phenotypes of heart disease. This study aims to evaluate a new DL algorithm for ...

Chest radiographs and machine learning - Past, present and future.

Journal of medical imaging and radiation oncology
Despite its simple acquisition technique, the chest X-ray remains the most common first-line imaging tool for chest assessment globally. Recent evidence for image analysis using modern machine learning points to possible improvements in both the effi...

Ligand Nanocluster Array Enables Artificial-Intelligence-Based Detection of Hidden Features in T-Cell Architecture.

Nano letters
Protein patterning has emerged as a powerful means to interrogate adhering cells. However, the tools to apply a sub-micrometer periodic stimulus and the analysis of the response are still being standardized. We propose a technique combining electron ...