United States Courses & Certifications

Towards Generalist Imaging Using Multimodal Self-Supervised Learning - Mars Huang

Exploring multimodal self-supervised learning for generalist medical imaging AI, addressing limitations of supervised learning and clinical context integration in automated image analysis.

• YouTube
• 58 minutes
• On-Demand
• Free Video

MedAI - Training Medical Image Segmentation Models with Less Labeled Data - Sarah Hooper

Innovative semi-supervised method for training medical image segmentation models using minimal labeled data, achieving comparable accuracy to fully supervised approaches while significantly reducing labeling requirements.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Observational Supervision for Medical Image Classification

Exploring gaze data as a novel supervision source for training deep learning models in medical image classification, focusing on chest X-rays and brain MRI scans for improved efficiency and accuracy.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Multimodal Medical Research of Vision and Language - Jean-Benoit Delbrouck

Explore multimodal medical research combining vision and language, focusing on innovative tasks like Medical Visual Question Answering and Radiology Report Generation using advanced AI architectures and pre-training techniques.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Self-Training - Weak Supervision Using Untrained Neural Nets for MR Reconstruction - Beliz Gunel

Exploring untrained neural networks for MR reconstruction, comparing self-training and weak supervision methods to improve performance with limited data while addressing slow inference times.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Multimodal Opportunistic Risk Assessment for Ischemic Heart Disease - Juan Manuel

Innovative approach integrating body composition biomarkers from CT scans with electronic medical records to enhance ischemic heart disease risk assessment, outperforming current clinical risk scores.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Mandoline - Model Evaluation under Distribution Shift

Explores a novel framework for evaluating machine learning models under distribution shifts, using slice-based reweighting to improve performance estimation on target distributions.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Rethinking Architecture Design for Data Heterogeneity in FL - Liangqiong Qu

Explores innovative architecture designs for federated learning in medical AI, focusing on Transformers to address data heterogeneity challenges and improve model performance across diverse healthcare institutions.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Frontiers of Medical AI - Therapeutics and Workflows

Explore cutting-edge AI applications in medicine, focusing on therapeutics and workflow optimization. Learn about AI-driven cancer treatment decisions, protein engineering, and specialized medical search engines.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Style Transfer Augmentations for Computational Pathology - Rikiya Yamashita

Innovative style transfer augmentation technique for improving machine learning model generalization in computational pathology, enhancing robustness to domain shifts and achieving state-of-the-art performance in classification tasks.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Learning the Structure of EHR with Graph Convolutional Transformer - Edward Choi

Explore graph convolutional transformers for learning EHR structure, combining graph convolution and self-attention for supervised prediction tasks in healthcare analytics and representation learning.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Patient-Specific COVID-19 Resource Utilization Prediction Using Fusion AI Model - Amara Tariq

Explore AI-driven prediction of COVID-19 resource utilization using fusion modeling, combining patient history and current indicators for efficient healthcare planning and allocation.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Self-Supervision & Contrastive Frameworks - A Vision-Based Review

Comprehensive review of self-supervised and contrastive learning frameworks in computer vision, exploring methodologies, performance, and potential applications in medical imaging.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Segmentation and Quantification of Breast Arterial Calcifications - Xiaoyuan Guo

Explore innovative techniques for segmenting and quantifying breast arterial calcifications in mammograms, aiming to improve cardiovascular risk assessment for women through non-invasive methods.

• YouTube
• 53 minutes
• On-Demand
• Free Video

Understanding Scanner Utilization with Metadata Extraction - Pradeeban Kathiravelu

Real-time DICOM metadata extraction for analyzing scanner utilization in radiology. Niffler framework enables accurate performance metrics, supports ML pipelines, and improves resource management in healthcare networks.

• YouTube
• 55 minutes
• On-Demand
• Free Video