AIMC Topic: Humans

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A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine.

Biomedical materials (Bristol, England)
Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem i...

Deep Semisupervised Multitask Learning Model and Its Interpretability for Survival Analysis.

IEEE journal of biomedical and health informatics
Survival analysis is a commonly used method in the medical field to analyze and predict the time of events. In medicine, this approach plays a key role in determining the course of treatment, developing new drugs, and improving hospital procedures. M...

CNN-MoE Based Framework for Classification of Respiratory Anomalies and Lung Disease Detection.

IEEE journal of biomedical and health informatics
This paper presents and explores a robust deep learning framework for auscultation analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from respiratory sound recordings. The framework begins with front-end feature ext...

Universal Physiological Representation Learning With Soft-Disentangled Rateless Autoencoders.

IEEE journal of biomedical and health informatics
Human computer interaction (HCI) involves a multidisciplinary fusion of technologies, through which the control of external devices could be achieved by monitoring physiological status of users. However, physiological biosignals often vary across use...

Deep Learning-Based Measurement of Total Plaque Area in B-Mode Ultrasound Images.

IEEE journal of biomedical and health informatics
Measurement of total-plaque-area (TPA) is important for determining long term risk for stroke and monitoring carotid plaque progression. Since delineation of carotid plaques is required, a deep learning method can provide automatic plaque segmentatio...

Explaining Black-Box Models for Biomedical Text Classification.

IEEE journal of biomedical and health informatics
In this paper, we propose a novel method named Biomedical Confident Itemsets Explanation (BioCIE), aiming at post-hoc explanation of black-box machine learning models for biomedical text classification. Using sources of domain knowledge and a confide...

Estimating Reference Bony Shape Models for Orthognathic Surgical Planning Using 3D Point-Cloud Deep Learning.

IEEE journal of biomedical and health informatics
Orthognathic surgical outcomes rely heavily on the quality of surgical planning. Automatic estimation of a reference facial bone shape significantly reduces experience-dependent variability and improves planning accuracy and efficiency. We propose an...

A Hierarchical Graph Convolution Network for Representation Learning of Gene Expression Data.

IEEE journal of biomedical and health informatics
The curse of dimensionality, which is caused by high-dimensionality and low-sample-size, is a major challenge in gene expression data analysis. However, the real situation is even worse: labelling data is laborious and time-consuming, so only a small...

Video-Based Detection of Generalized Tonic-Clonic Seizures Using Deep Learning.

IEEE journal of biomedical and health informatics
Timely detection of seizures is crucial to implement optimal interventions, and may help reduce the risk of sudden unexpected death in epilepsy (SUDEP) in patients with generalized tonic-clonic seizures (GTCSs). While video-based automated seizure de...

DeepUWF: An Automated Ultra-Wide-Field Fundus Screening System via Deep Learning.

IEEE journal of biomedical and health informatics
The emerging ultra-wide field of view (UWF) fundus color imaging is a powerful tool for fundus screening. However, manual screening is labor-intensive and subjective. Based on 2644 UWF images, a set of early fundus abnormal screening system named Dee...