AIMC Topic: Humans

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Rapid diagnosis of membranous nephropathy based on serum and urine Raman spectroscopy combined with deep learning methods.

Scientific reports
Membranous nephropathy is the main cause of nephrotic syndrome, which has an insidious onset and may progress to end-stage renal disease with a high mortality rate, such as renal failure and uremia. At present, the diagnosis of membranous nephropathy...

The use of deep learning for smartphone-based human activity recognition.

Frontiers in public health
The emerging field of digital phenotyping leverages the numerous sensors embedded in a smartphone to better understand its user's current psychological state and behavior, enabling improved health support systems for patients. As part of this work, a...

Application of Artificial Intelligence to Quantitative Assessment of Fundus Tessellated Density in Young Adults with Different Refractions.

Ophthalmic research
INTRODUCTION: The aim of this study was to quantitatively assess fundus tessellated density (FTD) and associated factors by artificial intelligence (AI) in young adults.

Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The clinical application of coronary MR angiography (MRA) remains limited due to its long acquisition time and often unsatisfactory image quality. A compressed sensing artificial intelligence (CSAI) framework was recently introduced to ov...

Raw Electroencephalogram-Based Cognitive Workload Classification Using Directed and Nondirected Functional Connectivity Analysis and Deep Learning.

Big data
With the phenomenal rise in internet-of-things devices, the use of electroencephalogram (EEG) based brain-computer interfaces (BCIs) can empower individuals to control equipment with thoughts. These allow BCI to be used and pave the way for pro-activ...

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy.

European radiology
OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a mode...

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

Medical & biological engineering & computing
The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms...

Robot-related fatalities at work in the United States, 1992-2017.

American journal of industrial medicine
BACKGROUND: Industrial robots became more commonplace in the US workplace during the mid- to latter part of the twentieth century. Recent scientific advances have led to the development of new types of robots, resulting in rapidly changing work envir...

Robot-assisted resection of multiple lung nodules through combination of intercostal incisions and a subxiphoid incision as a utility port.

The international journal of medical robotics + computer assisted surgery : MRCAS
INTRODUCTION: Robotic-assisted thoracic surgery (RATS) via subxiphoid incision may be superior in resection of multiple lung nodules.