AIMC Topic: Deep Learning

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A forensic evaluation method for DeepFake detection using DCNN-based facial similarity scores.

Forensic science international
Detecting DeepFake videos has become a central task in modern multimedia forensics applications. This article presents a method to detect face swapped videos when the portrayed person in the video is known. We propose using a threshold classifier bas...

Validation of a deep learning model for traumatic brain injury detection and NIRIS grading on non-contrast CT: a multi-reader study with promising results and opportunities for improvement.

Neuroradiology
PURPOSE: This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI).

External validation of a model for selecting day 3 embryos for transfer based upon deep learning and time-lapse imaging.

Reproductive biomedicine online
RESEARCH QUESTION: Could objective embryo assessment using iDAScore Version 2.0 perform as well as conventional morphological assessment?

Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
INTRODUCTION: The Laurén classification is widely used for Gastric Cancer (GC) histology subtyping. However, this classification is prone to interobserver variability and its prognostic value remains controversial. Deep Learning (DL)-based assessment...

Remora Namib Beetle Optimization Enabled Deep Learning for Severity of COVID-19 Lung Infection Identification and Classification Using CT Images.

Sensors (Basel, Switzerland)
Coronavirus disease 2019 (COVID-19) has seen a crucial outburst for both females and males worldwide. Automatic lung infection detection from medical imaging modalities provides high potential for increasing the treatment for patients to tackle COVID...

Pneumonia detection with QCSA network on chest X-ray.

Scientific reports
Worldwide, pneumonia is the leading cause of infant mortality. Experienced radiologists use chest X-rays to diagnose pneumonia and other respiratory diseases. The diagnostic procedure's complexity causes radiologists to disagree with the decision. Ea...

OSCA-finder: Redefining the assay of kidney disease diagnostic through metabolomics and deep learning.

Talanta
Liquid chromatography-mass spectrometry (LC-MS) is a platform for urine and blood sample analysis. However, the high variability in the urine sample reduced the confidence of metabolite identification. Therefore, pre and post-calibration operations a...

Enhancement of Non-Linear Deep Learning Model by Adjusting Confounding Variables for Bone Age Estimation in Pediatric Hand X-rays.

Journal of digital imaging
In medicine, confounding variables in a generalized linear model are often adjusted; however, these variables have not yet been exploited in a non-linear deep learning model. Sex plays important role in bone age estimation, and non-linear deep learni...

Noise reduction performance of a deep learning-based reconstruction in brain computed tomography images acquired with organ-based tube current modulation.

Physical and engineering sciences in medicine
We aimed to evaluate the image quality of brain computed tomography (CT) images reconstructed using deep learning-based reconstruction (DLR) in organ-based tube current modulation (OB-TCM) acquisition. An anthropomorphic head phantom and a cylindrica...

SCADA securing system using deep learning to prevent cyber infiltration.

Neural networks : the official journal of the International Neural Network Society
Supervisory Control and Data Acquisition (SCADA) systems are computer-based control architectures specifically engineered for the operation of industrial machinery via hardware and software models. These systems are used to project, monitor, and auto...