AIMC Topic: Humans

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Subsampled brain MRI reconstruction by generative adversarial neural networks.

Medical image analysis
A main challenge in magnetic resonance imaging (MRI) is speeding up scan time. Beyond improving patient experience and reducing operational costs, faster scans are essential for time-sensitive imaging, such as fetal, cardiac, or functional MRI, where...

Artificial Intelligence and Echocardiography: A Primer for Cardiac Sonographers.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Artificial intelligence (AI) is emerging as a key component in diagnostic medical imaging, including echocardiography. AI with deep learning has already been used with automated view labeling, measurements, and interpretation. As the development and ...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

American journal of medical genetics. Part A
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...

Chemists: AI Is Here; Unite To Get the Benefits.

Journal of medicinal chemistry
The latest developments in artificial intelligence (AI) have arrived into an existing state of creative tension between computational and medicinal chemists. At their most productive, medicinal and computational chemists have made significant progres...

Binary CorNET: Accelerator for HR Estimation From Wrist-PPG.

IEEE transactions on biomedical circuits and systems
Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commercial sensing modules, used widely for lifestyle monitoring. Reported methodologies have been fairly su...

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Oncogene
Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in cancer genomes occur due to internal and external mutagenesis forces. Decoding the mutational processes by examining their unique patterns has successfu...

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Nature communications
Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three in...

Electrical Impedance Tomography-Based Abdominal Subcutaneous Fat Estimation Method Using Deep Learning.

Computational and mathematical methods in medicine
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...

Age-Related Differences in the Uncanny Valley Effect.

Gerontology
BACKGROUND: Due to declining birthrates and an increasing aging population, shortage of the caregiving labor force has become a global issue. Among various efforts toward the solution, introducing robotic products for assistance could provide an effe...