Clinical Knowledge
18 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
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis
diku-dk/credanno
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Visualisation of the learned space further indicates that the correlation between the clustering of malignancy and nodule attributes coincides with clinical knowledge.
Knowledge-based Analysis for Mortality Prediction from CT Images
Recent studies have highlighted the high correlation between cardiovascular diseases (CVD) and lung cancer, and both are associated with significant morbidity and mortality.
Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics
Representation learning methods that transform encoded data (e. g., diagnosis and drug codes) into continuous vector spaces (i. e., vector embeddings) are critical for the application of deep learning in healthcare.
Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum
We derive a causal graph from the current clinical knowledge on cause and effect in the Alzheimer's disease continuum, and show that identifiability of the causal effect requires all confounders to be known and measured.
Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI
DIAGNijmegen/prostateMR_3D-CAD-csPCa
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We hypothesize that anatomical priors can be viable mediums to infuse domain-specific clinical knowledge into state-of-the-art convolutional neural networks (CNN) based on the U-Net architecture.
End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction
DIAGNijmegen/prostateMR_3D-CAD-csPCa
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We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model for automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR imaging (bpMRI).
Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis Treatment
Sepsis is a potentially life threatening inflammatory response to infection or severe tissue damage.
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
clinicalml/finding-decision-heterogeneity-regions
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NeurIPS 2021
Individuals often make different decisions when faced with the same context, due to personal preferences and background.
Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences
To overcome this, long sequence transformer models, e. g. Longformer and BigBird, were proposed with the idea of sparse attention mechanism to reduce the memory usage from quadratic to the sequence length to a linear scale.
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.
