AIMC Topic: Humans

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Early automated detection system for skin cancer diagnosis using artificial intelligent techniques.

Scientific reports
Recently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin cancer detection are painful, time-consuming, expensive, and may cause the disease to...

Explainability does not mitigate the negative impact of incorrect AI advice in a personnel selection task.

Scientific reports
Despite the rise of decision support systems enabled by artificial intelligence (AI) in personnel selection, their impact on decision-making processes is largely unknown. Consequently, we conducted five experiments (N = 1403 students and Human Resour...

Pediatric tympanostomy tube assessment via deep learning.

American journal of otolaryngology
PURPOSE: Tympanostomy tube (TT) placement is the most frequently performed ambulatory surgery in children under 15. After the procedure it is recommended that patients follow up regularly for "tube checks" until TT extrusion. Such visits incur direct...

Personalizing patient risk of a life-altering event: An application of machine learning to hemiarch surgery.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: The study objective was to assess a machine learning model's ability to predict the occurrence of life-altering events in hemiarch surgery and determine contributing patient characteristics and intraoperative factors.

Deep Learning Model for Grading and Localization of Lumbar Disc Herniation on Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Methods for grading and localization of lumbar disc herniation (LDH) on MRI are complex, time-consuming, and subjective. Utilizing deep learning (DL) models as assistance would mitigate such complexities.

Olecranon bone age assessment in puberty using a lateral elbow radiograph and a deep-learning model.

European radiology
OBJECTIVES: To improve pubertal bone age (BA) evaluation by developing a precise and practical elbow BA classification using the olecranon, and a deep-learning AI model.

Development and validation of a machine learning model to predict postoperative delirium using a nationwide database: A retrospective, observational study.

Journal of clinical anesthesia
STUDY OBJECTIVE: Postoperative delirium is a neuropsychological syndrome that typically occurs in surgical patients. Its onset can lead to prolonged hospitalization as well as increased morbidity and mortality. Therefore, it is important to promptly ...

High-performance deep spiking neural networks via at-most-two-spike exponential coding.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs) provide necessary models and algorithms for neuromorphic computing. A popular way of building high-performance deep SNNs is to convert ANNs to SNNs, taking advantage of advanced and well-trained ANNs. Here we propose an...

Multimodal information bottleneck for deep reinforcement learning with multiple sensors.

Neural networks : the official journal of the International Neural Network Society
Reinforcement learning has achieved promising results on robotic control tasks but struggles to leverage information effectively from multiple sensory modalities that differ in many characteristics. Recent works construct auxiliary losses based on re...