AIMC Topic: Algorithms

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Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen.

Tomography (Ann Arbor, Mich.)
The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the performance in conditions directly or indirectly affecting the spleen (e.g., splenomegaly, ascites). For ...

An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data.

Reproductive biology and endocrinology : RB&E
BACKGROUND: For the association between time-lapse technology (TLT) and embryo ploidy status, there has not yet been fully understood. TLT has the characteristics of large amount of data and non-invasiveness. If we want to accurately predict embryo p...

Automatic Robot-Driven 3D Reconstruction System for Chronic Wounds.

Sensors (Basel, Switzerland)
Chronic wounds, or wounds that are not healing properly, are a worldwide health problem that affect the global economy and population. Alongside with aging of the population, increasing obesity and diabetes patients, we can assume that costs of chron...

Packet Flow Capacity Autonomous Operation Based on Reinforcement Learning.

Sensors (Basel, Switzerland)
As the dynamicity of the traffic increases, the need for self-network operation becomes more evident. One of the solutions that might bring cost savings to network operators is the dynamic capacity management of large packet flows, especially in the ...

Hyper-fusion network for semi-automatic segmentation of skin lesions.

Medical image analysis
Segmentation of skin lesions is an important step for imaging-based clinical decision support systems. Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When the...

Feature Fusion of a Deep-Learning Algorithm into Wearable Sensor Devices for Human Activity Recognition.

Sensors (Basel, Switzerland)
This paper presents a wearable device, fitted on the waist of a participant that recognizes six activities of daily living (walking, walking upstairs, walking downstairs, sitting, standing, and laying) through a deep-learning algorithm, human activit...

Deep-learning-assisted algorithm for catheter reconstruction during MR-only gynecological interstitial brachytherapy.

Journal of applied clinical medical physics
Magnetic resonance imaging (MRI) offers excellent soft-tissue contrast enabling the contouring of targets and organs at risk during gynecological interstitial brachytherapy procedure. Despite its advantage, one of the main obstacles preventing a tran...

Accuracy Analysis of Feature-Based Automatic Modulation Classification via Deep Neural Network.

Sensors (Basel, Switzerland)
A feature-based automatic modulation classification (FB-AMC) algorithm has been widely investigated because of its better performance and lower complexity. In this study, a deep learning model was designed to analyze the classification performance of...

Biological features between miRNAs and their targets are unveiled from deep learning models.

Scientific reports
MicroRNAs (miRNAs) are ~ 22 nucleotide ubiquitous gene regulators. They modulate a broad range of essential cellular processes linked to human health and diseases. Consequently, identifying miRNA targets and understanding how they function are critic...

Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations.

Nature medicine
Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing concern that such AI systems may reflect and amplify human bias, and reduce the quality of their perfo...