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Found 7 papers, 0 papers with code
RegCLR: A Self-Supervised Framework for Tabular Representation Learning in the Wild
Recent advances in self-supervised learning (SSL) using large models to learn visual representations from natural images are rapidly closing the gap between the results produced by fully supervised learning and those produced by SSL on downstream vision tasks.
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?
The medical codes prediction problem from clinical notes has received substantial interest in the NLP community, and several recent studies have shown the state-of-the-art (SOTA) code prediction results of full-fledged deep learning-based methods.
Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines
Prediction of medical codes from clinical notes is both a practical and essential need for every healthcare delivery organization within current medical systems.
Ranked #4 on
Medical Code Prediction
on MIMIC-III
Medical Code Prediction
Multi-Label Classification Of Biomedical Texts
+1
Deep Claim: Payer Response Prediction from Claims Data with Deep Learning
Each year, almost 10% of claims are denied by payers (i. e., health insurance plans).
LumièreNet: Lecture Video Synthesis from Audio
We present Lumi\`ereNet, a simple, modular, and completely deep-learning based architecture that synthesizes, high quality, full-pose headshot lecture videos from instructor's new audio narration of any length.
Domain Adaptation for Real-Time Student Performance Prediction
Increasingly fast development and update cycle of online course contents, and diverse demographics of students in each online classroom, make student performance prediction in real-time (before the course finishes) and/or on curriculum without specific historical performance data available interesting topics for both industrial research and practical needs.
GritNet: Student Performance Prediction with Deep Learning
Student performance prediction - where a machine forecasts the future performance of students as they interact with online coursework - is a challenging problem.
