AI Medical Compendium

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

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Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

IEEE journal of biomedical and health informatics
Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable therapeutic effect in liver cancer. Compared with surgical resection, ablation treatment has a relatively high risk of tumor recurrence. To monitor tu...

Interactive Healthcare Robot Using Attention-Based Question-Answer Retrieval and Medical Entity Extraction Models.

IEEE journal of biomedical and health informatics
In healthcare facilities, answering the questions from the patients and their companions about the health problems is regarded as an essential task. With the current shortage of medical personnel resources and an increase in the patient-to-clinician ...

Large AI Models in Health Informatics: Applications, Challenges, and the Future.

IEEE journal of biomedical and health informatics
Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in vario...

Dynamic Corrected Split Federated Learning With Homomorphic Encryption for U-Shaped Medical Image Networks.

IEEE journal of biomedical and health informatics
U-shaped networks have become prevalent in various medical image tasks such as segmentation, and restoration. However, most existing U-shaped networks rely on centralized learning which raises privacy concerns. To address these issues, federated lear...

Stress Monitoring in Free-Living Environments.

IEEE journal of biomedical and health informatics
Stress monitoring is an important area of research with significant implications for individuals' physical and mental health. We present a data-driven approach for stress detection based on convolutional neural networks while addressing the problems ...

Fusion-Based Deep Learning Architecture for Detecting Drug-Target Binding Affinity Using Target and Drug Sequence and Structure.

IEEE journal of biomedical and health informatics
Accurately predicting drug-target binding affinity plays a vital role in accelerating drug discovery. Many computational approaches have been proposed due to costly and time-consuming of wet laboratory experiments. In the input representation, most m...

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.

IEEE journal of biomedical and health informatics
Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to severe complications such as bleeding and headache. Therefore, forecasting necrosis of the nasopharynx a...

Cross-Domain Unpaired Learning for Low-Dose CT Imaging.

IEEE journal of biomedical and health informatics
Supervised deep-learning techniques with paired training datasets have been widely studied for low-dose computed tomography (LDCT) imaging with excellent performance. However, the paired training datasets are usually difficult to obtain in clinical r...

Sleep Apnea Prediction Using Deep Learning.

IEEE journal of biomedical and health informatics
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...

Deep Learning in Surgical Workflow Analysis: A Review of Phase and Step Recognition.

IEEE journal of biomedical and health informatics
OBJECTIVE: In the last two decades, there has been a growing interest in exploring surgical procedures with statistical models to analyze operations at different semantic levels. This information is necessary for developing context-aware intelligent ...