AIMC Topic: Humans

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Transfer learning with convolutional neural networks for cancer survival prediction using gene-expression data.

PloS one
Precision medicine in oncology aims at obtaining data from heterogeneous sources to have a precise estimation of a given patient's state and prognosis. With the purpose of advancing to personalized medicine framework, accurate diagnoses allow prescri...

Assessing the environmental quality of an adapted, play-based LEGO robotics program to achieve optimal outcomes for children with disabilities.

Disability and rehabilitation
PURPOSE: This study assessed the environmental quality of an adapted, play-based LEGO robotics program for children and youth with disabilities to determine the degree to which the activity setting supports the therapeutic goals of the program.

Robot-Assisted Laparoscopic Urachal Excision Using Hidden Incision Endoscopic Surgery Technique in Pediatric Patients.

Journal of endourology
Although laparoscopic urachal excision in children has been well reported, there are limited data on a robot-assisted surgery (RAS) approach. The hidden incision endoscopic surgery (HIdES) technique is an established method of eliminating visible sc...

The Role and Promise of Artificial Intelligence in Medical Toxicology.

Journal of medical toxicology : official journal of the American College of Medical Toxicology
Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias...

Association of Cardiovascular Mortality and Deep Learning-Funduscopic Atherosclerosis Score derived from Retinal Fundus Images.

American journal of ophthalmology
PURPOSE: The prediction of atherosclerosis using retinal fundus images and deep learning has not been shown possible. The purpose of this study was to develop a deep learning model which predicted atherosclerosis by using retinal fundus images and to...

Data science and machine learning in anesthesiology.

Korean journal of anesthesiology
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with devel...

Learning in the machine: To share or not to share?

Neural networks : the official journal of the International Neural Network Society
Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sh...