AI Medical Compendium Journal:
IEEE reviews in biomedical engineering

Showing 1 to 10 of 41 articles

A Comprehensive Survey of Foundation Models in Medicine.

IEEE reviews in biomedical engineering
Foundation models (FMs) are large-scale deep learning models trained on massive datasets, often using self-supervised learning techniques. These models serve as a versatile base for a wide range of downstream tasks, including those in medicine and he...

Foundation Model for Advancing Healthcare: Challenges, Opportunities and Future Directions.

IEEE reviews in biomedical engineering
Foundation model, trained on a diverse range of data and adaptable to a myriad of tasks, is advancing healthcare. It fosters the development of healthcare artificial intelligence (AI) models tailored to the intricacies of the medical field, bridging ...

Artificial General Intelligence for Medical Imaging Analysis.

IEEE reviews in biomedical engineering
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models (LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of general domain tasks. Yet, when applied directly to specialized domains like m...

A Survey of Few-Shot Learning for Biomedical Time Series.

IEEE reviews in biomedical engineering
Advancements in wearable sensor technologies and the digitization of medical records have contributed to the unprecedented ubiquity of biomedical time series data. Data-driven models have tremendous potential to assist clinical diagnosis and improve ...

Data- and Physics-Driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies.

IEEE reviews in biomedical engineering
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans. This review elucidates recent advan...

Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions.

IEEE reviews in biomedical engineering
Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to improve the outcome of breast cancer patients. In the past decade, deep l...

Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities.

IEEE reviews in biomedical engineering
OBJECTIVE: Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. Wh...

Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence.

IEEE reviews in biomedical engineering
With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unpreced...

Beyond Supervised Learning for Pervasive Healthcare.

IEEE reviews in biomedical engineering
The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in healthcare data, namely scarcity, quality, and heterogeneity, hinder the effectiveness of supervised l...

A Review of Image-Based Food Recognition and Volume Estimation Artificial Intelligence Systems.

IEEE reviews in biomedical engineering
The daily healthy diet and balanced intake of essential nutrients play an important role in modern lifestyle. The estimation of a meal's nutrient content is an integral component of significant diseases, such as diabetes, obesity and cardiovascular d...