Medical & biological engineering & computing
Oct 22, 2018
Recently, researchers have built new deep learning (DL) models using a single image modality to diagnose age-related macular degeneration (AMD). Retinal fundus and optical coherence tomography (OCT) images in clinical settings are the most important ...
BACKGROUND: The average sensitivity of conventional cytology for the identification of cancer cells in effusion specimens is only approximately 58%. DNA image cytometry (DNA-ICM), which exploits the DNA content of morphologically suspicious nuclei me...
Mastering of medical knowledge to human is a lengthy process that typically involves several years of school study and residency training. Recently, deep learning algorithms have shown potential in solving medical problems. Here we demonstrate master...
Computational and mathematical methods in medicine
Oct 17, 2018
In this paper, a cosine similarity measure between hybrid intuitionistic fuzzy sets is proposed. The aim of the paper is to investigate the cosine similarity measure with hybrid intuitionistic fuzzy information and apply it to medical diagnosis. Firs...
BACKGROUND AND OBJECTIVE: Efficiently capturing the severity of positive valence symptoms could aid in risk stratification for adverse outcomes among patients with psychiatric disorders and identify optimal treatment strategies for patient subgroups....
Journal of the American College of Radiology : JACR
Oct 15, 2018
OBJECTIVES: With much hype about artificial intelligence (AI) rendering radiologists redundant, a simple radiologist-augmented AIÂ workflow is evaluated; the premise is that inclusion of a radiologist's opinion into an AI algorithm would make the algo...
Journal of voice : official journal of the Voice Foundation
Oct 11, 2018
The human voice production system is an intricate biological device capable of modulating pitch and loudness. Inherent internal and/or external factors often damage the vocal folds and result in some change of voice. The consequences are reflected in...
AJR. American journal of roentgenology
Oct 9, 2018
OBJECTIVE: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.
The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advance...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.