AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease.

IEEE journal of biomedical and health informatics
Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the inte...

An Improved Combination of Faster R-CNN and U-Net Network for Accurate Multi-Modality Whole Heart Segmentation.

IEEE journal of biomedical and health informatics
Detailed information of substructures of the whole heart is usually vital in the diagnosis of cardiovascular diseases and in 3D modeling of the heart. Deep convolutional neural networks have been demonstrated to achieve state-of-the-art performance i...

Estimation of Lower Extremity Joint Moments and 3D Ground Reaction Forces Using IMU Sensors in Multiple Walking Conditions: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Human kinetics, specifically joint moments and ground reaction forces (GRFs) can provide important clinical information and can be used to control assistive devices. Traditionally, collection of kinetics is mostly limited to the lab environment becau...

Predicting CircRNA-Disease Associations via Feature Convolution Learning With Heterogeneous Graph Attention Network.

IEEE journal of biomedical and health informatics
Exploring the relationship between circular RNA (circRNA) and disease is beneficial for revealing the mechanisms of disease pathogenesis. However, a blind search for all possible associations between circRNAs and diseases through biological experimen...

Explainable and Robust Deep Forests for EMG-Force Modeling.

IEEE journal of biomedical and health informatics
Machine and deep learning techniques have received increasing attentions in estimating finger forces from high-density surface electromyography (HDsEMG), especially for neural interfacing. However, most machine learning models are normally employed a...

A Methodology for a Scalable, Collaborative, and Resource-Efficient Platform, MERLIN, to Facilitate Healthcare AI Research.

IEEE journal of biomedical and health informatics
Healthcare artificial intelligence (AI) holds the potential to increase patient safety, augment efficiency and improve patient outcomes, yet research is often limited by data access, cohort curation, and tools for analysis. Collection and translation...

A Two-Branch Neural Network for Short-Axis PET Image Quality Enhancement.

IEEE journal of biomedical and health informatics
The axial field of view (FOV) is a key factor that affects the quality of PET images. Due to hardware FOV restrictions, conventional short-axis PET scanners with FOVs of 20 to 35 cm can acquire only low-quality PET (LQ-PET) images in fast scanning ti...

VLTENet: A Deep-Learning-Based Vertebra Localization and Tilt Estimation Network for Automatic Cobb Angle Estimation.

IEEE journal of biomedical and health informatics
Scoliosis diagnosis and assessment rely upon Cobb angle estimation from X-ray images of the spine. Recently, automated scoliosis assessment has been greatly improved using deep learning methods. However, in such methods, the Cobb angle is usually pre...

Microscopic Hyperspectral Image Classification Based on Fusion Transformer With Parallel CNN.

IEEE journal of biomedical and health informatics
Microscopic hyperspectral image (MHSI) has received considerable attention in the medical field. The wealthy spectral information provides potentially powerful identification ability when combining with advanced convolutional neural network (CNN). Ho...

Redefining Lobe-Wise Ground-Glass Opacity in COVID-19 Through Deep Learning and its Correlation With Biochemical Parameters.

IEEE journal of biomedical and health informatics
During COVID-19 pandemic qRT-PCR, CT scans and biochemical parameters were studied to understand the patients' physiological changes and disease progression. There is a lack of clear understanding of the correlation of lung inflammation with biochemi...