Latest AI and machine learning research in medicaid for healthcare professionals.
BACKGROUND: Convolutional neural networks (CNNs) have shown promising results in image denoising tas...
Gaze estimation is an established research problem in computer vision. It has various applications i...
Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that cou...
When a familial adenomatous polyposis (FAP) patient's rectal polyp undergoes malignant transformatio...
PURPOSE: Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shiel...
Computed tomography (CT) is widely used in clinical medicine, and low-dose CT (LDCT) has become popu...
Manual screening of Ziehl-Neelsen (ZN)-stained slides that are negative or contain rare acid-fast my...
Machine learning models have difficulty generalizing to data outside of the distribution they were t...
OBJECTIVE: To investigate the image quality and lesion conspicuity of a deep-learning-based contrast...
Indole-3-acetic acid (IAA) represents a crucial phytohormone regulating specific tropic responses in...
. Low-dose computed tomography (LDCT) denoising is an important problem in CT research. Compared to ...
Eye diseases that are common and many diseases that result in visual ailments, such as diabetes and ...
BACKGROUND: Reducing the radiation dose from computed tomography (CT) can significantly reduce the r...
BACKGROUND: To compare the quality of life (QOL) in patients who underwent robot-assisted radical pr...
Lowering the radiation dose in computed tomography (CT) can greatly reduce the potential risk to pub...
IMPORTANCE: Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but...
Deep learning, aided by the availability of big data sets, has led to substantial advances across ma...
In the biometric field, vein identification is a vital process that is constrained by the invisibili...
Biomimetic haptic neuron systems have received a lot of attention from the booming artificial intell...
BACKGROUND: The purpose of a convolutional neural network (CNN)-based denoiser is to increase the di...
To evaluate the performance of machine learning (ML) models and to compare it with logistic regressi...