Computational Phenotyping
6 papers with code • 0 benchmarks • 1 datasets
Computational Phenotyping is the process of transforming the noisy, massive Electronic Health Record (EHR) data into meaningful medical concepts that can be used to predict the risk of disease for an individual, or the response to drug therapy.
Source: Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis
Benchmarks
These leaderboards are used to track progress in Computational Phenotyping
Rare Diseases Mentions in MIMIC-III
Latest papers
Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records
jakeykj/cHITF
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Such methods generally require an input tensor describing the inter-modal interactions to be pre-established; however, the correspondence between different modalities (e. g., correspondence between medications and diagnoses) can often be missing in practice.
PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal
weitingchen83/Dehazing-PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal-TIP-2020
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IEEE Transaction on Image Processing 2020
In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.
Analysis | OPEN | Published: 17 June 2019 Multitask learning and benchmarking with clinical time series data
yerevann/mimic3-benchmarks
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Nature Scientific Data 2019
Health care is one of the most exciting frontiers in data mining and machine learning.
PMS-Net: Robust Haze Removal Based on Patch Map for Single Images
Conventional patch-based haze removal algorithms (e. g. the Dark Channel prior) usually performs dehazing with a fixed patch size.
Multitask learning and benchmarking with clinical time series data
yerevann/mimic3-benchmarks
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Health care is one of the most exciting frontiers in data mining and machine learning.
Unsupervised Learning for Computational Phenotyping
Hodapp87/mimic3_phenotyping
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With large volumes of health care data comes the research area of computational phenotyping, making use of techniques such as machine learning to describe illnesses and other clinical concepts from the data itself.
