AIMC Topic: Humans

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An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction.

Frontiers in public health
Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has therefore become an important research area to enhance patient survival rates. Several research studies have reported classification approaches for specific di...

Lightweight YOLOv4 with Multiple Receptive Fields for Detection of Pulmonary Tuberculosis.

Computational intelligence and neuroscience
The characteristics of pulmonary are complex, and the cost of manual screening is high. The detection model based on convolutional neural network is an essential method for assisted diagnosis with artificial intelligence. However, it also has the di...

Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks.

Computational intelligence and neuroscience
Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker's emotion from their words. Speech emotion recognition (SER) modules aid human-computer interface (HCI) applications, but they ar...

3D Virtual Modeling Realizations of Building Construction Scenes via Deep Learning Technique.

Computational intelligence and neuroscience
The architectural drawings of traditional building constructions generally require some design knowledge of the architectural plan to be understood. With the continuous development of the construction industry, the use of three-dimensional (3D) virtu...

Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries.

Journal of healthcare engineering
BACKGROUND: Dental caries is one of the major oral health problems and is increasing rapidly among people of every age (children, men, and women). Deep learning, a field of Artificial Intelligence (AI), is a growing field nowadays and is commonly use...

DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographs.

PloS one
Automatic detection of some pulmonary abnormalities using chest X-rays may be impacted adversely due to obscuring by bony structures like the ribs and the clavicles. Automated bone suppression methods would increase soft tissue visibility and enhance...

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been...

Robot-assisted and conventional urology surgical procedures: comparison of average length of stay, economic status, operative time and patient's expenditure in a tertiary care hospital of North India.

Journal of robotic surgery
Robot-assisted surgeries allows the surgeons to operate using remote-controlled robotic arms that are more effective in comparison to conventional (open/laparoscopic) surgeries. However, there is substantial lack of evidence on the effectiveness of r...

Deep learning for automatic segmentation of paraspinal muscle on computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.

Development of an affordable, immersive model for robotic vaginal cuff closure: a randomized trial.

Journal of robotic surgery
Safe and secure closure of the vaginal cuff is a critical component of a robotic assisted hysterectomy procedure. Our aim in this study is to develop and validate a novel vaginal cuff closure model (VC) created from porcine heart that allows trainees...