AIMC Topic: Humans

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BFENet: A two-stream interaction CNN method for multi-label ophthalmic diseases classification with bilateral fundus images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Early fundus screening and timely treatment of ophthalmology diseases can effectively prevent blindness. Previous studies just focus on fundus images of single eye without utilizing the useful relevant information of the lef...

The Gastrohepatic Ligament Approach in Robotic Spleen-Preserving Distal Pancreatectomy with Resection of the Splenic Vessels: The Superior Window Approach in the Warshaw Technique.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: There have been few studies reporting on the surgical approaches of minimally invasive spleen-preserving distal pancreatectomy (SPDP). Herein, we present two cases who underwent robotic SPDP with resection of the splenic vessels using our...

[Artificial intelligence (AI) in radiology? : Do we need as many radiologists in the future?].

Der Urologe. Ausg. A
We are in the middle of a digital revolution in medicine. This raises the question of whether subjects such as radiology, which is superficially concerned with the interpretation of images, will be particularly changed by this revolution. In particul...

Automated diagnosis of age-related macular degeneration using multi-modal vertical plane feature fusion via deep learning.

Medical physics
PURPOSE: To develop a computer-aided diagnostic (CADx) system of age-related macular degeneration (AMD) through feature fusion between infrared reflectance (IR) and optical coherence tomography (OCT) modalities in order to explore the superiority of ...

Bayesian modeling of human-AI complementarity.

Proceedings of the National Academy of Sciences of the United States of America
SignificanceWith the increase in artificial intelligence in real-world applications, there is interest in building hybrid systems that take both human and machine predictions into account. Previous work has shown the benefits of separately combining ...

Recreating the Motion Trajectory of a System of Articulated Rigid Bodies on the Basis of Incomplete Measurement Information and Unsupervised Learning.

Sensors (Basel, Switzerland)
Re-creating the movement of an object consisting of articulated rigid bodies is an issue that concerns both mechanical and biomechanical systems. In the case of biomechanical systems, movement re-storation allows, among other things, introducing chan...

A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance.

Sensors (Basel, Switzerland)
This paper presents a comprehensive overview of current deep-learning methods for automatic object classification of underwater sonar data for shoreline surveillance, concentrating mostly on the classification of vessels from passive sonar data and t...

A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium.

Scientific reports
The aim of this study is to test whether sex prediction can be made by using machine learning algorithms (ML) with parameters taken from computerized tomography (CT) images of cranium and mandible skeleton which are known to be dimorphic. CT images o...

Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges.

Arthritis research & therapy
Histopathology is widely used to analyze clinical biopsy specimens and tissues from pre-clinical models of a variety of musculoskeletal conditions. Histological assessment relies on scoring systems that require expertise, time, and resources, which c...

Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.

BMC cancer
BACKGROUND: Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival...