AI Medical Compendium Journal:
Medical & biological engineering & computing

Showing 131 to 140 of 330 articles

Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture.

Medical & biological engineering & computing
Prediction of the stage of cancer plays an important role in planning the course of treatment and has been largely reliant on imaging tools which do not capture molecular events that cause cancer progression. Gene-expression data-based analyses are a...

AEAU-Net: an unsupervised end-to-end registration network by combining affine transformation and deformable medical image registration.

Medical & biological engineering & computing
Deformable medical image registration plays an essential role in clinical diagnosis and treatment. However, due to the large difference in image deformation, unsupervised convolutional neural network (CNN)-based methods cannot extract global features...

Hardware deployment of deep learning model for classification of breast carcinoma from digital mammogram images.

Medical & biological engineering & computing
Cancer is an illness that instils fear in many individuals throughout the world due to its lethal nature. However, in most situations, cancer may be cured if detected early and treated properly. Computer-aided diagnosis is gaining traction because it...

FiMec tremor stabilization spoon: design and active stabilization control of two DoF robotic eating devices for hand tremor patients.

Medical & biological engineering & computing
This article is about vibration-damping robotic eating devices designed for use by people who have difficulty in eating due to hand tremors due to neuromuscular system disorder. The robotic eating device has two degrees of freedom (DoF). It contains ...

A weakly supervised method for named entity recognition of Chinese electronic medical records.

Medical & biological engineering & computing
The field of Chinese medical natural language processing faces a significant challenge in training accurate entity recognition models due to the limited availability of high-quality labeled data. In response, we propose a joint training model, MCBERT...

Plane invariant segmentation of computed tomography images through weighted cross entropy optimized conditional GANs in compressed formats.

Medical & biological engineering & computing
Computed tomography (CT) scan provides first-hand knowledge to doctors to identify an ailment. Deep neural networks help enhance image understanding through segmentation and labeling. In this work, we implement two variants of Pix2Pix generative adve...

Collision avoidance analysis of human-robot physical interaction based on null-space impedance control of a dynamic reference arm plane.

Medical & biological engineering & computing
When the terminal upper limb rehabilitation robot is used for motion-assisted training, collisions between the manipulator links and the human upper limb may occur due to the null-space self-motion of the redundant manipulator. A null-space impedance...

Transformer-based temporal sequence learners for arrhythmia classification.

Medical & biological engineering & computing
An electrocardiogram (ECG) plays a crucial role in identifying and classifying cardiac arrhythmia. Traditional methods employ handcrafted features, and more recently, deep learning methods use convolution and recursive structures to classify heart si...

A membership-function-based broad learning system for human-robot interaction force estimation under drawing task.

Medical & biological engineering & computing
Estimating interaction force is of great significance in the field of human-robot interaction (HRI) thanks to its guarantee of interaction safety. To this end, this paper proposes a novel estimation method by leveraging broad learning system (BLS) an...

Comparison of four machine learning algorithms for a pre-impact fall detection system.

Medical & biological engineering & computing
In recent years, real-time health monitoring using wearable sensors has been an active area of research. This paper presents an efficient and low-cost fall detection system based on a pair of shoes equipped with inertial sensors and plantar pressure ...