Incorporating prior domain knowledge into deep neural networks
In recent years, the large amount of labeled data available has also helped tend research
toward using minimal domain knowledge, eg, in deep neural network research. However, in …
toward using minimal domain knowledge, eg, in deep neural network research. However, in …
Explainable stacking-based model for predicting hospital readmission for diabetic patients
Artificial intelligence is changing the practice of healthcare. While it is essential to employ
such solutions, making them transparent to medical experts is more critical. Most of the …
such solutions, making them transparent to medical experts is more critical. Most of the …
A stacking-based model for predicting 30-day all-cause hospital readmissions of patients with acute myocardial infarction
Z Zhang, H Qiu, W Li, Y Chen - BMC medical informatics and decision …, 2020 - Springer
Background Acute myocardial infarction (AMI) is a serious cardiovascular disease, followed
by a high readmission rate within 30-days of discharge. Accurate prediction of AMI …
by a high readmission rate within 30-days of discharge. Accurate prediction of AMI …
Mt-gcn for multi-label audio-tagging with noisy labels
Multi-label audio tagging is the task of predicting the types of sounds occurring in an audio
clip. Recently, large-scale audio datasets such as Google's AudioSet, have allowed …
clip. Recently, large-scale audio datasets such as Google's AudioSet, have allowed …
QSAR Models for Active Substances against Pseudomonas aeruginosa Using Disk-Diffusion Test Data
Pseudomonas aeruginosa is a Gram-negative bacillus included among the six “ESKAPE”
microbial species with an outstanding ability to “escape” currently used antibiotics and …
microbial species with an outstanding ability to “escape” currently used antibiotics and …
A framework for integrating domain knowledge in logistic regression with application to hospital readmission prediction
It is commonly understood that machine learning algorithms discover and extract knowledge
based on data at hand. However, a huge amount of knowledge is available which is in …
based on data at hand. However, a huge amount of knowledge is available which is in …
Profiling environmental conditions from DNA
DNA is quintessential to carry out basic functions by organisms as it encodes information
necessary for metabolomics and proteomics, among others. In particular, it is common …
necessary for metabolomics and proteomics, among others. In particular, it is common …
A Roadmap to Domain Knowledge Integration in Machine Learning
Many machine learning algorithms have been developed in recent years to enhance the
performance of a model in different aspects of artificial intelligence. But the problem persists …
performance of a model in different aspects of artificial intelligence. But the problem persists …
[PDF][PDF] Domain knowledge infusion in machine learning for digital signal processing applications
C Wieland - Master's thesis, 2021 - scholar.archive.org
This work explores the infusion of domain knowledge as a way to improve machine learning
applications in signal processing. Table tennis stroke detection is used here as an in-depth …
applications in signal processing. Table tennis stroke detection is used here as an in-depth …
Estimating Average and Individual Treatment Effects in the Presence of Time-Dependent Covariates
The causal inference in survival analysis framework provides a comprehensive evaluation of
survival probabilities, considering the influence of time-dependent covariates. Incorporating …
survival probabilities, considering the influence of time-dependent covariates. Incorporating …