Foundation model for cancer imaging biomarkers
Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
Multimodal healthcare AI: identifying and designing clinically relevant vision-language applications for radiology
Recent advances in AI combine large language models (LLMs) with vision encoders that
bring forward unprecedented technical capabilities to leverage for a wide range of …
bring forward unprecedented technical capabilities to leverage for a wide range of …
Open challenges and opportunities in federated foundation models towards biomedical healthcare
X Li, L Peng, YP Wang, W Zhang - BioData Mining, 2025 - Springer
This survey explores the transformative impact of foundation models (FMs) in artificial
intelligence, focusing on their integration with federated learning (FL) in biomedical …
intelligence, focusing on their integration with federated learning (FL) in biomedical …
Value Proposition of Retinal Imaging in Alzheimer's Disease Screening: A Review of Eight Evolving Trends
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Current diagnostic
modalities of AD generally focus on detecting the presence of amyloid β and tau protein in …
modalities of AD generally focus on detecting the presence of amyloid β and tau protein in …
Map** the individual, social and biospheric impacts of Foundation Models
A Domínguez Hernández, S Krishna… - The 2024 ACM …, 2024 - dl.acm.org
Responding to the rapid roll-out and large-scale commercialization of foundation models,
large language models, and generative AI, an emerging body of work is shedding light on …
large language models, and generative AI, an emerging body of work is shedding light on …
Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit
Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet
innovation teams struggle when envisioning AI concepts. Data science teams think of …
innovation teams struggle when envisioning AI concepts. Data science teams think of …
Investigating Why Clinicians Deviate from Standards of Care: Liberating Patients from Mechanical Ventilation in the ICU
N Yildirim, S Zlotnikov, A Venkat, G Chawla… - Proceedings of the CHI …, 2024 - dl.acm.org
Clinical practice guidelines, care pathways, and protocols are designed to support evidence-
based practices for clinicians; however, their adoption remains a challenge. We set out to …
based practices for clinicians; however, their adoption remains a challenge. We set out to …
Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination
Traditional interventions for academic procrastination often fail to capture the nuanced,
individual-specific factors that underlie them. Large language models (LLMs) hold immense …
individual-specific factors that underlie them. Large language models (LLMs) hold immense …
Leveraging foundation and large language models in medical artificial intelligence
Recent advancements in the field of medical artificial intelligence (AI) have led to the
widespread adoption of foundational and large language models. This review paper …
widespread adoption of foundational and large language models. This review paper …
On Robustness-Accuracy Characterization of Large Language Models using Synthetic Datasets
In recent years, large language models (LLMs) that were pretrained at scale on diverse data
have proven to be a successful approach for solving different downstream tasks. However …
have proven to be a successful approach for solving different downstream tasks. However …