AI Medical Compendium

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

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Decentralized Data-Privacy Preserving Deep-Learning Approaches for Enhancing Inter-Database Generalization in Automatic Sleep Staging.

IEEE journal of biomedical and health informatics
Automatic sleep staging has been an active field of development. Despite multiple efforts, the area remains a focus of research interest. Indeed, while promising results have reported in past literature, uptake of automatic sleep scoring in the clini...

Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning.

IEEE journal of biomedical and health informatics
PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-invasive techniques such as resting-state functional magnetic resonance imaging (rs-fMRI) have been proven valuable in early AD diagnosis. This study inv...

Semi-Supervised Learning for Low-Cost Personalized Obstructive Sleep Apnea Detection Using Unsupervised Deep Learning and Single-Lead Electrocardiogram.

IEEE journal of biomedical and health informatics
OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can lead to a wide range of health issues if left untreated. This study aims to address the lack of research on personalized models for single-lead electrocard...

Digital Twin in Healthcare: A Study for Chronic Wound Management.

IEEE journal of biomedical and health informatics
Although the concept of digital twin technology has been in existence for nearly half a century, its application in healthcare is a relatively recent development. In healthcare, the utilization of digital twin and data-driven models has proven to enh...

Cooperative Learning for Personalized Context-Aware Pain Assessment From Wearable Data.

IEEE journal of biomedical and health informatics
Despite the promising performance of automated pain assessment methods, current methods suffer from performance generalization due to the lack of relatively large, diverse, and annotated pain datasets. Further, the majority of current methods do not ...

Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation.

IEEE journal of biomedical and health informatics
The Healthcare Internet-of-Things (IoT) framework aims to provide personalized medical services with edge devices. Due to the inevitable data sparsity on an individual device, cross-device collaboration is introduced to enhance the power of distribut...

Leveraging Summary Guidance on Medical Report Summarization.

IEEE journal of biomedical and health informatics
This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50 K, 16 K and 378 K pairs of report and summary that are derived from MIMIC-III, respectively. We implement convincing baselines o...

An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence.

IEEE journal of biomedical and health informatics
Difficulty in knowledge validation is a significant hindrance to knowledge discovery via data mining, especially automatic validation without artificial participation. In the field of medical research, medical knowledge discovery from electronic medi...

Federated Semi-Supervised Learning for Medical Image Segmentation via Pseudo-Label Denoising.

IEEE journal of biomedical and health informatics
Distributed big data and digital healthcare technologies have great potential to promote medical services, but challenges arise when it comes to learning predictive model from diverse and complex e-health datasets. Federated Learning (FL), as a colla...

A Novel Deep Learning Model for Medical Report Generation by Inter-Intra Information Calibration.

IEEE journal of biomedical and health informatics
Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the mo...