The impact of artificial intelligence in the odyssey of rare diseases
Emerging machine learning (ML) technologies have the potential to significantly improve the
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
[HTML][HTML] The role of artificial intelligence in prediction, risk stratification, and personalized treatment planning for congenital heart diseases
This narrative review delves into the potential of artificial intelligence (AI) in predicting,
stratifying risk, and personalizing treatment planning for congenital heart disease (CHD) …
stratifying risk, and personalizing treatment planning for congenital heart disease (CHD) …
A clinical text classification paradigm using weak supervision and deep representation
Background Automatic clinical text classification is a natural language processing (NLP)
technology that unlocks information embedded in clinical narratives. Machine learning …
technology that unlocks information embedded in clinical narratives. Machine learning …
Diagnosis support systems for rare diseases: a scoping review
Introduction Rare diseases affect approximately 350 million people worldwide. Delayed
diagnosis is frequent due to lack of knowledge of most clinicians and a small number of …
diagnosis is frequent due to lack of knowledge of most clinicians and a small number of …
Recommended practices and ethical considerations for natural language processing‐assisted observational research: a scoping review
An increasing number of studies have reported using natural language processing (NLP) to
assist observational research by extracting clinical information from electronic health records …
assist observational research by extracting clinical information from electronic health records …
Improving rare disease classification using imperfect knowledge graph
Background Accurately recognizing rare diseases based on symptom description is an
important task in patient triage, early risk stratification, and target therapies. However, due to …
important task in patient triage, early risk stratification, and target therapies. However, due to …
Why is misdiagnosis more likely among some people with rare diseases than others? Insights from a population-based cross-sectional study in China
D Dong, RYN Chung, RHW Chan, S Gong… - Orphanet journal of rare …, 2020 - Springer
Background For patients with rare diseases (RD), misdiagnosis (or erroneous diagnosis) is
one of the key issues that hinder RD patients' accessibility to timely treatment. Yet, little is …
one of the key issues that hinder RD patients' accessibility to timely treatment. Yet, little is …
[HTML][HTML] HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology
Background In precision medicine, deep phenotyping is defined as the precise and
comprehensive analysis of phenotypic abnormalities, aiming to acquire a better …
comprehensive analysis of phenotypic abnormalities, aiming to acquire a better …
Rare disease knowledge enrichment through a data-driven approach
Background Existing resources to assist the diagnosis of rare diseases are usually curated
from the literature that can be limited for clinical use. It often takes substantial effort before …
from the literature that can be limited for clinical use. It often takes substantial effort before …
[HTML][HTML] Utilization of electronic medical records and biomedical literature to support the diagnosis of rare diseases using data fusion and collaborative filtering …
Background: In the United States, a rare disease is characterized as the one affecting no
more than 200,000 patients at a certain period. Patients suffering from rare diseases are …
more than 200,000 patients at a certain period. Patients suffering from rare diseases are …