Semantic information retrieval on medical texts: Research challenges, survey, and open issues
The explosive growth and widespread accessibility of medical information on the Internet
have led to a surge of research activity in a wide range of scientific communities including …
have led to a surge of research activity in a wide range of scientific communities including …
[HTML][HTML] Explainable automated coding of clinical notes using hierarchical label-wise attention networks and label embedding initialisation
Background Diagnostic or procedural coding of clinical notes aims to derive a coded
summary of disease-related information about patients. Such coding is usually done …
summary of disease-related information about patients. Such coding is usually done …
Graph neural networks for clinical risk prediction based on electronic health records: A survey
Objective: This study aims to comprehensively review the use of graph neural networks
(GNNs) for clinical risk prediction based on electronic health records (EHRs). The primary …
(GNNs) for clinical risk prediction based on electronic health records (EHRs). The primary …
Genhpf: General healthcare predictive framework for multi-task multi-source learning
Despite the remarkable progress in the development of predictive models for healthcare,
applying these algorithms on a large scale has been challenging. Algorithms trained on a …
applying these algorithms on a large scale has been challenging. Algorithms trained on a …
Metacare++: Meta-learning with hierarchical subty** for cold-start diagnosis prediction in healthcare data
Cold-start diagnosis prediction is a challenging task for AI in healthcare, where often only a
few visits per patient and a few observations per disease can be exploited. Although meta …
few visits per patient and a few observations per disease can be exploited. Although meta …
Sequential diagnosis prediction with transformer and ontological representation
Sequential diagnosis prediction on the Electronic Health Record (EHR) has been proven
crucial for predictive analytics in the medical domain. EHR data, sequential records of a …
crucial for predictive analytics in the medical domain. EHR data, sequential records of a …
Time-aware context-gated graph attention network for clinical risk prediction
Clinical risk prediction based on Electronic Health Records (EHR) can assist doctors in
better judgment and can make sense of early diagnosis. However, the prediction …
better judgment and can make sense of early diagnosis. However, the prediction …
Investigating patterns of change, stability, and interaction among scientific disciplines using embeddings
Multi-disciplinary and inter-disciplinary collaboration can be an appropriate response to
tackling the increasingly complex problems faced by today's society. Scientific disciplines …
tackling the increasingly complex problems faced by today's society. Scientific disciplines …
Contrastive learning of temporal distinctiveness for survival analysis in electronic health records
M Nayebi Kerdabadi… - Proceedings of the …, 2023 - dl.acm.org
Survival analysis plays a crucial role in many healthcare decisions, where the risk prediction
for the events of interest can support an informative outlook for a patient's medical journey …
for the events of interest can support an informative outlook for a patient's medical journey …
Medical provider embeddings for healthcare fraud detection
Advances in data mining and machine learning continue to transform the healthcare industry
and provide value to medical professionals and patients. In this study, we address the …
and provide value to medical professionals and patients. In this study, we address the …