AIMC Topic: Humans

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Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.

Journal of medical systems
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...

A novel deep learning approach to classify 3D foot types of diabetic patients.

Scientific reports
Diabetes mellitus is a worldwide epidemic that leads to significant changes in foot shape, deformities, and ulcers. Precise classification of diabetic foot not only helps identify foot abnormalities but also facilitates personalized treatment and pre...

Reinforcement learning-driven automated head and neck simultaneous integrated boost (SIB) radiation therapy: flexible treatment planning aligned with clinical preferences.

Physics in medicine and biology
Head-and-neck simultaneous integrated boost (SIB) treatment planning using intensity modulated radiation therapy is particularly challenging due to the proximity to organs-at-risk. Depending on the specific clinical conditions, different parotid-spar...

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.

Physics in medicine and biology
Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely...

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages.

Biomedical physics & engineering express
. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-quality training datasets. However, they cannot fully replace the conventional optimization process. Thi...

Miniaturized soft growing robots for minimally invasive surgeries: challenges and opportunities.

Progress in biomedical engineering (Bristol, England)
Advancements in assistive robots have significantly transformed healthcare procedures in recent years. Clinical continuum robots have enhanced minimally invasive surgeries, offering benefits to patients such as reduced blood loss and a short recovery...

Optimized glaucoma detection using HCCNN with PSO-driven hyperparameter tuning.

Biomedical physics & engineering express
. This study is focused on creating an effective glaucoma detection system employing a Hybrid Centric Convolutional Neural Network (HCCNN) model. By using Particle Swarm Optimization (PSO), classification accuracy is increased and computing complexit...

A semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.

Physics in medicine and biology
Prostate lesion segmentation from multiparametric magnetic resonance images is particularly challenging due to the limited availability of labeled data. This scarcity of annotated images makes it difficult for supervised models to learn the complex f...

Advancing Single-Plane Wave Ultrasound Imaging With Implicit Multiangle Acoustic Synthesis via Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Plane wave imaging (PWI) is pivotal in medical ultrasound (US), prized for its ultrafast capabilities essential for real-time physiological monitoring. Traditionally, enhancing image quality in PWI has necessitated an increase in the number of plane ...

MM-UKAN++: A Novel Kolmogorov-Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (ROIs) in US images is essential for enhancing the efficiency of clinical and robot-assisted diagnosis...