AIMC Topic: Humans

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Automatic lower limb bone segmentation in radiographs with different orientations and fields of view based on a contextual network.

International journal of computer assisted radiology and surgery
PURPOSE: Bone identification and segmentation in X-ray images are crucial in orthopedics for the automation of clinical procedures, but it often involves some manual operations. In this work, using a modified SegNet neural network, we automatically i...

Analyzing factors contributing to COVID-19 mortality in the United States using artificial intelligence techniques.

Risk analysis : an official publication of the Society for Risk Analysis
Having started since late 2019, COVID-19 has spread through far many nations around the globe. Not being known profoundly, the novel virus of the Coronaviruses family has already caused more than half a million deaths and put the lives of many more p...

Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing.

Yearbook of medical informatics
OBJECTIVES: Analyze the content of publications within the medical natural language processing (NLP) domain in 2021.

An open source pipeline for quantitative immunohistochemistry image analysis of inflammatory skin disease using artificial intelligence.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: The application of artificial intelligence (AI) to whole slide images has the potential to improve research reliability and ultimately diagnostic efficiency and service capacity. Image annotation plays a key role in AI and digital patholo...

Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction.

Medical physics
BACKGROUND: Motion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBC...

Deetect: A Deep Learning-Based Image Analysis Tool for Quantification of Adherent Cell Populations on Oxygenator Membranes after Extracorporeal Membrane Oxygenation Therapy.

Biomolecules
The strong interaction of blood with the foreign surface of membrane oxygenators during ECMO therapy leads to adhesion of immune cells on the oxygenator membranes, which can be visualized in the form of image sequences using confocal laser scanning m...

Ensemble of RNN Classifiers for Activity Detection Using a Smartphone and Supporting Nodes.

Sensors (Basel, Switzerland)
Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities accurately. However, the accuracy of the existing activity recognition methods decreases rapidly if the set of activities is extended and includes training routines, s...

Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area.

Scientific reports
Ground subsidence caused by natural factors, including groundwater, has been extensively researched. However, there have been few studies on ground sink caused mainly by artifacts, including underground pipelines in urban areas. This paper proposes a...

Introduction.

Best practice & research. Clinical gastroenterology
Endoscopic ultrasound (EUS) was born from the combination of a high-frequency ultrasound probe with an endoscope to assess in detail the walls of the upper and lower gastrointestinal tract and surrounding organs and structures. The subsequent possibi...

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

British journal of neurosurgery
INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate deep learning and transfer learning in the prediction of several inpatient outcomes including timing...