AIMC Topic: Humans

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Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos.

Medical image analysis
Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action triplet recognition stands out as the only one aiming to provide truly fine-grained and comprehensive information on surgical activities. This information, pre...

PhenoRerank: A re-ranking model for phenotypic concept recognition pre-trained on human phenotype ontology.

Journal of biomedical informatics
The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database to train our mo...

Dose prediction via distance-guided deep learning: Initial development for nasopharyngeal carcinoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Geometric information such as distance information is essential for dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use only binary masks without distance information. This study aims to de...

Physicians' preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists.

BMC health services research
BACKGROUND: Artificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologis...

Prognosis patients with COVID-19 using deep learning.

BMC medical informatics and decision making
BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensi...

Development and quantitative assessment of deep learning-based image enhancement for optical coherence tomography.

BMC ophthalmology
PURPOSE: To develop a deep learning-based framework to improve the image quality of optical coherence tomography (OCT) and evaluate its image enhancement effect with the traditional image averaging method from a clinical perspective.

Robot-assisted Simple Prostatectomy Is Better than Endoscopic Enucleation of the Prostate.

European urology focus
Robot-assisted simple prostatectomy represents a solid treatment option for benign prostatic obstruction in patients with large prostate glands. This procedure offers multiple attractive features that make it a strong competitor against endoscopic en...

Premature Ventricular Contraction Recognition Based on a Deep Learning Approach.

Journal of healthcare engineering
Electrocardiogram signal (ECG) is considered a significant biological signal employed to diagnose heart diseases. An ECG signal allows the demonstration of the cyclical contraction and relaxation of human heart muscles. This signal is a primary and n...

Effective CBMIR System Using Hybrid Features-Based Independent Condensed Nearest Neighbor Model.

Journal of healthcare engineering
In recent times, a large number of medical images are generated, due to the evolution of digital imaging modalities and computer vision application. Due to variation in the shape and size of the images, the retrieval task becomes more tedious in the ...

A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients.

Journal of healthcare engineering
In today's scenario, sepsis is impacting millions of patients in the intensive care unit due to the fact that the mortality rate is increased exponentially and has become a major challenge in the field of healthcare. Such peoples require determinant ...