AIMC Topic: Humans

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Hypergraph learning for identification of COVID-19 with CT imaging.

Medical image analysis
The coronavirus disease, named COVID-19, has become the largest global public health crisis since it started in early 2020. CT imaging has been used as a complementary tool to assist early screening, especially for the rapid identification of COVID-1...

COVID-AL: The diagnosis of COVID-19 with deep active learning.

Medical image analysis
The efficient diagnosis of COVID-19 plays a key role in preventing the spread of this disease. The computer-aided diagnosis with deep learning methods can perform automatic detection of COVID-19 using CT scans. However, large scale annotation of CT s...

Accuracy of dental implant surgery with robotic position feedback and registration algorithm: An in-vitro study.

Computers in biology and medicine
BACKGROUND: The purpose of this study was to develop and validate a positioning method with hand-guiding and contact position feedback of robot based on a human-robot collaborative dental implant system (HRCDIS) for robotic guided dental implant surg...

Deep learning segmentation of Primary Sjögren's syndrome affected salivary glands from ultrasonography images.

Computers in biology and medicine
Salivary gland ultrasonography (SGUS) has proven to be a promising tool for diagnosing various diseases manifesting with abnormalities in salivary glands (SGs), including primary Sjögren's syndrome (pSS). At present, the major obstacle for establishi...

Significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
OBJECTIVES: This study aims to identify significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia.

Predicting the risk of developing diabetic retinopathy using deep learning.

The Lancet. Digital health
BACKGROUND: Diabetic retinopathy screening is instrumental to preventing blindness, but scaling up screening is challenging because of the increasing number of patients with all forms of diabetes. We aimed to create a deep-learning system to predict ...

Recognized trophoblast-like cells conversion from human embryonic stem cells by BMP4 based on convolutional neural network.

Reproductive toxicology (Elmsford, N.Y.)
The use of models of stem cell differentiation to trophoblastic cells provides an effective perspective for understanding the early molecular events in the establishment and maintenance of human pregnancy. In combination with the newly developed deep...

Artificial Intelligence and Acute Stroke Imaging.

AJNR. American journal of neuroradiology
Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention to reduce ...

Estimating Local Cellular Density in Glioma Using MR Imaging Data.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which ce...