AIMC Topic: Humans

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Enhancing classification of cells procured from bone marrow aspirate smears using generative adversarial networks and sequential convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Leukemia represents 30% of all pediatric cancers and is considered the most common malignancy affecting adults and children. Cell differential count obtained from bone marrow aspirate smears is crucial for diagnosing hematol...

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations, and Experiences.

Molecular nutrition & food research
With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) becomes a new scientific field and the first commercial offerings of genotype-ba...

Industrializing AI-powered drug discovery: lessons learned from the computing platform.

Expert opinion on drug discovery
INTRODUCTION: As a mid-size international pharmaceutical company, we initiated 4 years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named ' was built up on the initial predicate to capitaliz...

Building Process-Oriented Data Science Solutions for Real-World Healthcare.

International journal of environmental research and public health
The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help h...

Full Soft Capacitive Omnidirectional Tactile Sensor Based on Micro-Spines Electrode and Hemispheric Dielectric Structure.

Biosensors
Flourishing in recent years, intelligent electronics is desirably pursued in many fields including bio-symbiotic, human physiology regulatory, robot operation, and human-computer interaction. To support this appealing vision, human-like tactile perce...

Automatic Identification of Depression Using Facial Images with Deep Convolutional Neural Network.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Depression is a common disease worldwide, with about 280 million people having depression. The unique facial features of depression provide a basis for automatic recognition of depression with deep convolutional neural networks. MATERIAL A...

Deep Learning-Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists
PURPOSE: Modern endovascular hybrid operating rooms generate large amounts of medical images during a procedure, which are currently mostly assessed by eye. In this paper, we present fully automatic segmentation of the stent graft on the completion d...

Commercially Available Deep-learning-reconstruction of MR Imaging of the Knee at 1.5T Has Higher Image Quality Than Conventionally-reconstructed Imaging at 3T: A Normal Volunteer Study.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: This study aimed to evaluate whether the image quality of 1.5T magnetic resonance imaging (MRI) of the knee is equal to or higher than that of 3T MRI by applying deep learning reconstruction (DLR).

Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Studies have identified imaging markers of binge drinking. Functional connectivity during both task challenges and resting state was shown to distinguish binge and nonbinge drinkers. However, no studies have compared the efficacy of task ...