Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
The healthcare field is undergoing a profound shift, with deep learning in AI increasingly augmenting medical expertise in complex and challenging tasks. Our research addresses the challenging task of chest X-ray image diagnostics, a field characterized by multifaceted diagnostic labels and class im-balances in respiratory disease cases. Our approach synergizes a pre-trained image classification n...
In the realm of healthcare where decentralized facilities are prevalent, machine learning faces two major challenges concerning the protection of data and models. The data-level challenge concerns the data privacy leakage when centralizing data with sensitive personal information. While the model-level challenge arises from the heterogeneity of local models, which need to be collaboratively trai...
The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Art...
Deep feedforward and recurrent neural networks have become successful functional models of the brain, but they neglect obvious biological details such...
Virtually unknown to the greater public before November 2022, ChatGPT was made available in open access in Autumn 2022, driving the perspective of art...
BACKGROUND: Accurate segmentation of liver tumor regions in medical images is of great significance for clinical diagnosis and the planning of surgica...
Blood oxygen level dependent (BOLD) MRI time series with maternal hyperoxia can assess placental oxygenation and function. Measuring precise BOLD chan...
The Hermite wavelet method (HWM) is introduced in this study to solve a nonlinear differential equation determining the human corneal morphology. The ...
With the demand for sophisticated techniques to easily prevent the deflection of needles, robotic CT (computed tomography)-guided puncture with an ult...
The growing accessibility of large health datasets and AI's ability to analyze them offers significant potential to transform public health and epidem...
In 2006, Japan's pharmaceutical science education was revised to a 6-year enrollment course, placing greater emphasis on cultivating practical clinica...
Internal medicine departments must adapt their structures and methods of operation to accommodate changing healthcare systems. The present paper discu...
Minimally invasive instruments are inserted per-cutaneously and are steered toward the desired anatomy. The low stiffness of instruments is an advanta...
A neural network-assisted molecular dynamics method is developed to reduce the computational cost of open boundary simulations. Particle influxes and ...
The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because...
Colorectal cancer has become the second leading cause of cancer-related death, attracting considerable interest for automatic polyp segmentation in po...
MOTIVATION: Mapping distal regulatory elements, such as enhancers, is a cornerstone for elucidating how genetic variations may influence diseases. Pre...
To overcome the computational burden of processing three-dimensional (3D) medical scans and the lack of spatial information in two-dimensional (2D) me...
The rapid development of artificial intelligence (AI) and digital health raise concerns about equitable access to innovative interventions, appropriat...
OBJECTIVE: To assess the clinical effectiveness of boundary recognition of upper abdomen organs on CT images based on neural network model and the com...