AIMC Topic: Humans

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Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.

Toxicologic pathology
Digital tissue image analysis is a computational method for analyzing whole-slide images and extracting large, complex, and quantitative data sets. However, as with any analysis method, the quality of generated results is dependent on a well-designed...

Transfer learning with pre-trained deep convolutional neural networks for the automatic assessment of liver steatosis in ultrasound images.

Medical ultrasonography
AIM: In this paper we proposed different architectures of convolutional neural network (CNN) to classify fatty liver disease in images using only pixels and diagnosis labels as input. We trained and validated our models using a dataset of 629 images ...

Lung cancer survival period prediction and understanding: Deep learning approaches.

International journal of medical informatics
INTRODUCTION: Survival period prediction through early diagnosis of cancer has many benefits. It allows both patients and caregivers to plan resources, time and intensity of care to provide the best possible treatment path for the patients. In this p...

Smooth dendrite morphological neurons.

Neural networks : the official journal of the International Neural Network Society
A typical feature of hyperbox-based dendrite morphological neurons (DMN) is the generation of sharp and rough decision boundaries that inaccurately track the distribution shape of classes of patterns. This feature is because the minimum and maximum a...

Quantization Friendly MobileNet (QF-MobileNet) Architecture for Vision Based Applications on Embedded Platforms.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have become popular for various applications in the domain of image and computer vision due to their well-established performance attributes. DNN algorithms involve powerful multilevel feature extractions resulting in an e...

A Head-to Head Comparison of Machine Learning Algorithms for Identification of Implanted Cardiac Devices.

The American journal of cardiology
Application of artificial intelligence techniques in medicine has rapidly expanded in recent years. Two algorithms for identification of cardiac implantable electronic devices using chest radiography were recently developed: The PacemakerID algorithm...

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

International journal of cancer
Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRLM) to surgery or conservative therapy. However, there is no well-recognized method for predicting pa...

Safety critical event prediction through unified analysis of driver and vehicle volatilities: Application of deep learning methods.

Accident; analysis and prevention
Transportation safety is highly correlated with driving behavior, especially human error playing a key role in a large portion of crashes. Modern instrumentation and computational resources allow for the monitorization of driver, vehicle, and roadway...

The Co-Pilot Project: An International Neurosurgical Collaboration in Ukraine.

World neurosurgery
OBJECTIVE: We aim to provide a thorough description of the efforts and outcomes of the Co-Pilot Project in Ukraine, which facilitates neurosurgical collaboration between American and Ukrainian physicians.

Does Robot Navigation and Intraoperative Computed Tomography Guidance Help with Percutaneous Endoscopic Lumbar Discectomy? A Match-Paired Study.

World neurosurgery
OBJECTIVE: To evaluate the efficacy and safety of robot-assisted percutaneous endoscopic lumbar discectomy (rPELD) using a specially designed orthopaedic robot with an intraoperative computed tomography-equipped suite for treatment of symptomatic lum...