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An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

Journal of hepatology
BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Our aims were to develop and validate an artificial intelligence-assisted prediction model of...

Use of artificial intelligence for gender bias analysis in letters of recommendation for general surgery residency candidates.

American journal of surgery
BACKGROUND: Letters of recommendation (LoRs) play an important role in resident selection. Author language varies implicitly toward male and female applicants. We examined gender bias in LoRs written for surgical residency candidates across three dec...

Clinical Validation of a Deep Learning-Based Hybrid (Greulich-Pyle and Modified Tanner-Whitehouse) Method for Bone Age Assessment.

Korean journal of radiology
OBJECTIVE: To evaluate the accuracy and clinical efficacy of a hybrid Greulich-Pyle (GP) and modified Tanner-Whitehouse (TW) artificial intelligence (AI) model for bone age assessment.

Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning.

NeuroImage
Whether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy ...

Noninvasive intracranial pressure real-time waveform analysis monitor during prostatectomy robotic surgery and Trendelenburg position: case report.

Brazilian journal of anesthesiology (Elsevier)
Both robotic surgery and head-down tilt increase intracranial pressure by impairing venous blood outflow. Prostatectomy is commonly performed in elderly patients, who are more likely to develop postoperative cognitive disorders. Therefore, increased ...

Retrospective study of deep learning to reduce noise in non-contrast head CT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PURPOSE: Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framework with group convolutions and a novel loss function to improve the subjective and objective image quality for improved disease detection in patients...

Data-driven electrophysiological feature based on deep learning to detect epileptic seizures.

Journal of neural engineering
. To identify a new electrophysiological feature characterising the epileptic seizures, which is commonly observed in different types of epilepsy.. We recorded the intracranial electroencephalogram (iEEG) of 21 patients (12 women and 9 men) with mult...

Utilizing data sampling techniques on algorithmic fairness for customer churn prediction with data imbalance problems.

F1000Research
Customer churn prediction (CCP) refers to detecting which customers are likely to cancel the services provided by a service provider, for example, internet services. The class imbalance problem (CIP) in machine learning occurs when there is a huge d...