AIMC Topic: Humans

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A meta-learning algorithm for respiratory flow prediction from FBG-based wearables in unrestrained conditions.

Artificial intelligence in medicine
The continuous monitoring of an individual's breathing can be an instrument for the assessment and enhancement of human wellness. Specific respiratory features are unique markers of the deterioration of a health condition, the onset of a disease, fat...

Health Index Estimation of Wind Power Plant Using Neurofuzzy Modeling.

Computational and mathematical methods in medicine
According to the Tamil Nadu Energy Development Agency (TEDA) in the 2019-20 academic year, the wind power plant produces 23% of the biomass power supply in the Indian electrical commodities. To maintain the power withstanding capability needed for fu...

Long Jump Action Recognition Based on Deep Convolutional Neural Network.

Computational intelligence and neuroscience
Long jump is a test item of national student physical health monitoring, which can reflect the quality of students' lower limb strength. Long jump is a highly technical activity, which includes four basic movements: running aid, jumping, vacating, an...

Can images crowdsourced from the internet be used to train generalizable joint dislocation deep learning algorithms?

Skeletal radiology
OBJECTIVE: Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of these injuries, collecting large numbers of images to train algorithms may be infeasible for many cen...

Intuitive endoscopic robot master device with image orientation correction.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The camera of an endoscope is fixed to the device, and the image rotates together with the endoscope. This can lead to visual confusion for the user and incorrect image reading. The problem also occurs with endoscopic robots. Using a mast...

Robot assisted laparoscopic adrenalectomy: Should this be the new standard?

Urologia
INTRODUCTION: Minimal invasive surgeries (MIS) for large size adrenal tumors are still debatable. The objective is to evaluate the contemporary peri- and post-operative outcomes of patients undergoing (open = OA, laparoscopic = LA, and robotic = RA) ...

Deep learning architectures for Parkinson's disease detection by using multi-modal features.

Computers in biology and medicine
BACKGROUND: The use of multi-modal features for improving the diagnosing accuracy of Parkinson's disease (PD) is still under consideration.

idse-HE: Hybrid embedding graph neural network for drug side effects prediction.

Journal of biomedical informatics
In drug development, unexpected side effects are the main reason for the failure of candidate drug trials. Discovering potential side effects of drugsin silicocan improve the success rate of drug screening. However, most previous works extracted and ...

3D laparoscopic prostatectomy: results of multicentre study.

Scandinavian journal of urology
INTRODUCTION: Three-dimensional laparoscopic prostatectomy (3D LRP) is a potentially cost-effective option for robot-assisted laparoscopic prostatectomy (RALP). Results for two-dimensional LRP and RALP are well documented; however, little has been pu...

A Combined Semi-Supervised Deep Learning Method for Oil Leak Detection in Pipelines Using IIoT at the Edge.

Sensors (Basel, Switzerland)
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in immeas...