Clinical Knowledge
26 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Clinical Knowledge
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BIG-bench
Most implemented papers
Auto-Gait: Automatic Ataxia Risk Assessment with Computer Vision on Gait Task Videos
In this paper, we investigated whether we can 1) detect participants with ataxia-specific gait characteristics (risk-prediction), and 2) assess severity of ataxia from gait (severity-assessment) using computer vision.
Learning to Revise References for Faithful Summarization
In real-world scenarios with naturally occurring datasets, reference summaries are noisy and may contain information that cannot be inferred from the source text.
Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network
Automatic ECG classification methods, especially the deep learning based ones, have been proposed to detect cardiac abnormalities using ECG records, showing good potential to improve clinical diagnosis and help early prevention of cardiovascular diseases.
Trial2Vec: Zero-Shot Clinical Trial Document Similarity Search using Self-Supervision
We propose a zero-shot clinical trial retrieval method, Trial2Vec, which learns through self-supervision without annotating similar clinical trials.
CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models
styfeng/chard
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We motivate and introduce CHARD: Clinical Health-Aware Reasoning across Dimensions, to investigate the capability of text generation models to act as implicit clinical knowledge bases and generate free-flow textual explanations about various health-related conditions across several dimensions.
A Comparative Study of Pretrained Language Models for Long Clinical Text
Objective: Clinical knowledge enriched transformer models (e. g., ClinicalBERT) have state-of-the-art results on clinical NLP (natural language processing) tasks.
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals
ss-sun/attri-net
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Furthermore, as we show in this paper, current explanation techniques do not perform adequately in the multi-label scenario, in which multiple medical findings may co-occur in a single image.
Dual-view Correlation Hybrid Attention Network for Robust Holistic Mammogram Classification
BryantGary/IJCAI23-Dual-view-Correlation-Hybrid-Attention-Network
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Mammogram image is important for breast cancer screening, and typically obtained in a dual-view form, i. e., cranio-caudal (CC) and mediolateral oblique (MLO), to provide complementary information.
Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training
To address these issues, we propose the Knowledge-Boosting Contrastive Vision-Language Pre-training framework (KoBo), which integrates clinical knowledge into the learning of vision-language semantic consistency.
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models
Clinical natural language processing requires methods that can address domain-specific challenges, such as complex medical terminology and clinical contexts.
