AIMC Topic: Humans

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Deep learning-based defects detection of certain aero-engine blades and vanes with DDSC-YOLOv5s.

Scientific reports
When performed by a person, aero-engine borescope inspection is easily influenced by individual experience and human factors that can lead to incorrect maintenance decisions, potentially resulting in serious disasters, as well as low efficiency. To a...

A deep learning framework for epileptic seizure detection based on neonatal EEG signals.

Scientific reports
Electroencephalogram (EEG) is one of the main diagnostic tests for epilepsy. The detection of epileptic activity is usually performed by a human expert and is based on finding specific patterns in the multi-channel electroencephalogram. This is a dif...

A Novel Deep Learning Model to Distinguish Malignant Versus Benign Solid Lung Nodules.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND In this study we aimed to establish a new transfer learning model based on noncontrast and thin-layer computed tomography (CT) scans to distinguish between malignant and benign solid lung nodules. MATERIAL AND METHODS CT images from 202 pa...

Snowflake: A deep learning-based human leukocyte antigen matching algorithm considering allele-specific surface accessibility.

Frontiers in immunology
Histocompatibility in solid-organ transplantation has a strong impact on long-term graft survival. Although recent advances in matching of both B-cell epitopes and T-cell epitopes have improved understanding of allorecognition, the immunogenic determ...

Simulation Analysis and Study of Gait Stability Related to Motion Joints.

BioMed research international
Gait stability in exercise is an inevitable and vexing problem in mechanics, artificial intelligence, sports, and rehabilitation medicine research. With the rapid development and popularization of science and technology, it becomes a reality for rese...

Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.

PloS one
Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic ...

SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep is a vital process of our daily life as we roughly spend one-third of our lives asleep. In order to evaluate sleep quality and potential sleep disorders, sleep stage classification is a gold standard method. In this paper, we introduce a novel ...

Reacting and responding to rare, uncertain and unprecedented events.

Ergonomics
This work examines how we may be able to anticipate, respond to, and train for the occurrence of rare, uncertain, and unexpected events in human-machine systems operations. In particular, it uses a foundational matrix which describes the combinations...

Laparoscopic versus robotic inguinal hernia repair: a single-center case-matched study.

Surgical endoscopy
INTRODUCTION: Robotic inguinal hernia repair (RIHR) is becoming increasingly common and is the minimally invasive alternative to laparoscopic inguinal hernia repair (LIHR). Thus far, there is little data directly comparing LIHR and RIHR. The purpose ...