AIMC Topic: Humans

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Intuitive Spatial Tactile Feedback for Better Awareness about Robot Trajectory during Human-Robot Collaboration.

Sensors (Basel, Switzerland)
In this work, we extend the previously proposed approach of improving mutual perception during human-robot collaboration by communicating the robot's motion intentions and status to a human worker using hand-worn haptic feedback devices. The improvem...

Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode.

Sensors (Basel, Switzerland)
Advances in robotics are part of reducing the burden associated with manufacturing tasks in workers. For example, the cobot could be used as a "third-arm" during the assembling task. Thus, the necessity of designing new intuitive control modalities a...

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...

Explainable machine-learning predictions for complications after pediatric congenital heart surgery.

Scientific reports
The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of thera...

Predicting postoperative pain following root canal treatment by using artificial neural network evaluation.

Scientific reports
This study aimed to evaluate the accuracy of back propagation (BP) artificial neural network model for predicting postoperative pain following root canal treatment (RCT). The BP neural network model was developed using MATLAB 7.0 neural network toolb...

Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey.

Journal of medical Internet research
BACKGROUND: Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to health care. However, for the successful implementation of AI, large amounts of health data are required for training and testin...

Using machine learning and big data to explore the drug resistance landscape in HIV.

PLoS computational biology
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...

Deep Learning for Intelligent Recognition and Prediction of Endometrial Cancer.

Journal of healthcare engineering
The aim of the study was to investigate the intelligent recognition of radiomics based on the convolutional neural network (CNN) in predicting endometrial cancer (EC). In this study, 158 patients with EC in hospital were selected as the research obje...

Developing a Robotic General Surgery Training Curriculum: Identifying Key Elements Through a Delphi Process.

Journal of surgical education
OBJECTIVE: A national robotic surgery curriculum is still developing for general surgery residents as robotic surgery becomes increasingly accessible. One general surgery residency program utilized a Delphi process to optimize a robotic surgery curri...

Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN).

PloS one
The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate due to risks of breast cancer. Early detection of cancer boosts increasing the survival chance up t...