AIMC Topic: Humans

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The stability investigation of variable viscosity control in the human-robot interaction.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: For many co-manipulative applications, variable damping is a valuable feature provided by robots. One approach is implementing a high viscosity at low velocities and a low viscosity at high velocities. This, however, is proven to have the...

Use of artificial intelligence in emergency radiology: An overview of current applications, challenges, and opportunities.

Clinical imaging
The value of artificial intelligence (AI) in healthcare has become evident, especially in the field of medical imaging. The accelerated pace and acuity of care in the Emergency Department (ED) has made it a popular target for artificial intelligence-...

Objective and Subjective Assessment of Bladder Function after Robot-assisted Laparoscopic Radical Hysterectomy for Early-stage Cervical Cancer.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To examine whether objective bladder function after robot-assisted radical hysterectomy (RRH) for early-stage cervical cancer is correlated with subjective patient-reported outcomes and quality of life during the first year after RRH...

ThoraciNet: thoracic abnormality detection and disease classification using fusion DCNNs.

Physical and engineering sciences in medicine
Chest X-rays are arguably the de facto medical imaging technique for diagnosing thoracic abnormalities. Chest X-ray analysis is complex, especially in asymptomatic diseases, and relies heavily on the expertise of radiologists. This work proposes the ...

Deep learning techniques for liver and liver tumor segmentation: A review.

Computers in biology and medicine
Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, and kidneys complicate li...

HGSORF: Henry Gas Solubility Optimization-based Random Forest for C-Section prediction and XAI-based cause analysis.

Computers in biology and medicine
A stable predictive model is essential for forecasting the chances of cesarean or C-section (CS) delivery, as unnecessary CS delivery can adversely affect neonatal, maternal, and pediatric morbidity and mortality, and can incur significant financial ...

ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction.

Nature methods
Predicting the functional sites of a protein from its structure, such as the binding sites of small molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two classes of methods prevail: machine learning models built...

Risk assessment of ICU patients through deep learning technique: A big data approach.

Journal of global health
BACKGROUND: Intensive Care Unit (ICU) patients are exposed to various medications, especially during infusion, and the amount of infusion drugs and the rate of their application may negatively affect their health status. A deep learning model can mon...

Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning.

Sensors (Basel, Switzerland)
The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals' emotions empowers sentiment analysis. However, sentiment analysis becomes even mo...

Integration of Digital Twin, Machine-Learning and Industry 4.0 Tools for Anomaly Detection: An Application to a Food Plant.

Sensors (Basel, Switzerland)
This work describes a structured solution that integrates digital twin models, machine-learning algorithms, and Industry 4.0 technologies (Internet of Things in particular) with the ultimate aim of detecting the presence of anomalies in the functioni...