AIMC Topic: Humans

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Current Trends in the Utilization of a Robotic Approach in the Field of Bariatric Surgery.

Obesity surgery
PURPOSE: The utilization rate of robotic surgery for bariatric procedures is not well-described. Our study identified the proportion of metabolic and bariatric surgery (MBS) procedures in the United States between 2015 and 2020 performed using a robo...

Accuracy of computer-assisted pedicle screw placement for adolescent idiopathic scoliosis: a comparison between robotics and navigation.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To compare the accuracy of pedicle screw placement in adolescent idiopathic scoliosis (AIS) between robotics and navigation and clarify the factors that cause screw deviation when robotics is used.

Artificial Intelligence-Assisted Digital Immunoassay Based on a Programmable-Particle-Decoding Technique for Multitarget Ultrasensitive Detection.

Analytical chemistry
The development of a multitarget ultrasensitive immunoassay is significant to fields such as medical research, clinical diagnosis, and food safety inspection. In this study, an artificial intelligence (AI)-assisted programmable-particle-decoding tech...

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

EBioMedicine
BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.

Cooperative Hand Therapy via a Soft, Wearable, and Unilateral Telerobotic System.

IEEE transactions on bio-medical engineering
Functional rehabilitation of the hand is a complex and difficult process involving a large number of degrees of freedom (DOFs). Soft wearable hand-rehabilitation robots have assisted hand movements with a compact structural design, but effective reha...

Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

IEEE transactions on bio-medical engineering
The availability of large amounts of data from continuous glucose monitoring (CGM), together with the latest advances in deep learning techniques, have opened the door to a new paradigm of algorithm design for personalized blood glucose (BG) predicti...

An Unobtrusive Human Activity Recognition System Using Low Resolution Thermal Sensors, Machine and Deep Learning.

IEEE transactions on bio-medical engineering
Given the aging population, healthcare systems need to be established to deal with health issues such as injurious falls. Wearable devices can be used to detect falls. However, most wearable devices are obtrusive, and patients generally do not like o...

Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach.

Genes
Genetic disorders are the result of mutation in the deoxyribonucleic acid (DNA) sequence which can be developed or inherited from parents. Such mutations may lead to fatal diseases such as Alzheimer's, cancer, Hemochromatosis, etc. Recently, the use ...

Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

Sensors (Basel, Switzerland)
The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for early diagnosis and treatment. However, since ADHD is not a simple disease that can be diagnosed with a...

Hybrid Target Selections by "Hand Gestures + Facial Expression" for a Rehabilitation Robot.

Sensors (Basel, Switzerland)
In this study we propose a "hand gesture + face expression" human machine interaction technique, and apply this technique to bedridden rehabilitation robot. "Hand gesture + Facial expression" interactive technology combines the input mode of gesture ...