In recent times, as interest in stress control has increased, many studies on stress recognition have been conducted. Several studies have been based on physiological signals, but the disadvantage of this strategy is that it requires physiological-si...
In this study, a fluorescent biosensor was developed for the sensitive detection of typhimurium using a low-gradient magnetic field and deep learning via faster region-based convolutional neural networks (R-CNN) to recognize the fluorescent spots on...
Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with w...
INTRODUCTION: Deep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people's medical cond...
Megavoltage computed tomography (MV-CT) is used for setup verification and adaptive radiotherapy in tomotherapy. However, its low contrast and high noise lead to poor image quality. This study aimed to develop a deep-learning-based method to generate...
Computational intelligence and neuroscience
Nov 11, 2021
At night, buoys and other navigation marks disappear to be replaced by fixed or flashing lights. Navigation marks are seen as a set of lights in various colors rather than their familiar outline. Deciphering that the meaning of the lights is a burden...
Computational intelligence and neuroscience
Nov 11, 2021
BACKGROUND: Leukemia is fatal cancer in both children and adults and is divided into acute and chronic. Acute lymphoblastic leukemia (ALL) is a subtype of this cancer. Early diagnosis of this disease can have a significant impact on the treatment of ...
Cellularity estimation forms an important aspect of the visual examination of bone marrow biopsies. In clinical practice, cellularity is estimated by eye under a microscope, which is rapid, but subjective and subject to inter- and intraobserver varia...
AJR. American journal of roentgenology
Nov 10, 2021
Convolutional neural networks (CNNs) trained to identify abnormalities on upper extremity radiographs achieved an AUC of 0.844 with a frequent emphasis on radiograph laterality and/or technologist labels for decision-making. Covering the labels incre...
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