This study demonstrates how the new-age technologies, such as GenAI and Natura Language Processing (NLP) can aid in collecting valuable clinical data, improving patient safety and rare disease identification, as well as integrating natural language processing and graph-based reasoning to enhance disease recognition.
This work demonstrates how AI-driven informatics can enhance rare disease diagnosis and exemplifies the role of digital tools in transforming precision medicine and healthcare delivery.
J. Pérez-García, Federico García-Criado, F. Pazos et al.· iScience· 0 citations
With rare diseases affecting 350 million people worldwide, medical knowledge and new drug development remain inconsistently spread between diseases. The PLUTO mission, a pioneering International Rare Diseases Research Consortium initiative, seeks to advance understanding of the current level of knowledge through...
D. Ardigò, Francesco Bianchi, Maria Cristina Bosio et al.· Orphanet Journal of Rare Dis...· 0 citations
The proposed methodology selects and preprocesses a large corpus of scientific articles on malaria, and then annotates them with entities of clinical significance, and leverages BioBERT, a state-of-the-art pre-trained language model, to encode the textual data into context-aware representations.
Background: Rare diseases affect an estimated 300 million people worldwide, yet the research needed to guide diagnosis and treatment is often fragmented across multiple unstructured literature sources. Natural history studies (NHS) are a key source of this evidence, but manually extracting structured information from N...
An ontology-guided framework that integrates a Knowledge Graph, an Ontology-Informed Retrieval Classifier, and a Large Language Model for interpretable mental health detection from social media text demonstrates that the KG–ORC cross-validation gate measurably improves predictive reliability over single component basel...
Amina Tahir, Ghulam Mustafa, Muhammad Tanvir Afzal et al.· Social Network Analysis and...· 0 citations
Originating in India, Ayurveda is an ancient medical system focused on holistic healing that considers the mind, body, and spirit. This study utilizes knowledge graph (KG) technology to develop a KG model for an Ayurveda question-and-answer system. The system includes modules for knowledge extraction from चरकसंहिता, का...
Sharayu Mirasdar, Dr Mangesh Bedekar· International Journal of Inf...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
