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Found 11 papers, 5 papers with code
A Linguistic Annotation Framework to Study Interactions in Multilingual Healthcare Conversational Forums
In recent years, remote digital healthcare using online chats has gained momentum, especially in the Global South.
Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support
Advances in artificial intelligence (AI) are enabling systems that augment and collaborate with humans to perform simple, mechanistic tasks like scheduling meetings and grammar-checking text.
Applications and Techniques for Fast Machine Learning in Science
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery.
Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach
Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context.
A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support
We develop a novel unifying theoretically-grounded framework for characterizing the communication of empathy in text-based conversations.
Embedding-based Retrieval in Facebook Search
In this paper, we discuss the techniques for applying EBR to a Facebook Search system.
A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology Images
Executing machine learning (ML) pipelines in real-time on radiology images is hard due to the limited computing resources in clinical environments and the lack of efficient data transfer capabilities to run them on research clusters.
DeepAISE -- An End-to-End Development and Deployment of a Recurrent Neural Survival Model for Early Prediction of Sepsis
Sepsis, a dysregulated immune system response to infection, is among the leading causes of morbidity, mortality, and cost overruns in the Intensive Care Unit (ICU).
Feature Extraction Based Machine Learning for Human Burn Diagnosis From Burn Images
The 74 images of test data set are tested with the proposed SVM based method and according to the ground truth, the accuracy of 82. 43% was achieved for the SVM based model, which was higher than the 79. 73% achieved in past work using the multidimensional scaling analysis (MDS) approach
Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer
Quantitative assessment of Tumor-TIL spatial relationships is increasingly important in both basic science and clinical aspects of breast cancer research.
Improving Latent User Models in Online Social Media
Modern social platforms are characterized by the presence of rich user-behavior data associated with the publication, sharing and consumption of textual content.
