AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Rare Diseases

Showing 71 to 80 of 111 articles

Clear Filters

Towards the automated economic assessment of newborn screening for rare diseases.

Journal of biomedical informatics
OBJECTIVE: Economic assessments of newborn screening programs for rare diseases involve the use of models and require huge efforts to synthesize information from different sources. Sharing and automatically or semi-automatically reusing this informat...

Rare disease knowledge enrichment through a data-driven approach.

BMC medical informatics and decision making
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 the suspicion of a rare disease is even raised to utilize t...

Xrare: a machine learning method jointly modeling phenotypes and genetic evidence for rare disease diagnosis.

Genetics in medicine : official journal of the American College of Medical Genetics
PURPOSE: Despite the successful progress next-generation sequencing technologies has achieved in diagnosing the genetic cause of rare Mendelian diseases, the current diagnostic rate is still far from satisfactory because of heterogeneity, imprecision...

DeepNEU: cellular reprogramming comes of age - a machine learning platform with application to rare diseases research.

Orphanet journal of rare diseases
BACKGROUND: Conversion of human somatic cells into induced pluripotent stem cells (iPSCs) is often an inefficient, time consuming and expensive process. Also, the tendency of iPSCs to revert to their original somatic cell type over time continues to ...

An ontological foundation for ocular phenotypes and rare eye diseases.

Orphanet journal of rare diseases
BACKGROUND: The optical accessibility of the eye and technological advances in ophthalmic diagnostics have put ophthalmology at the forefront of data-driven medicine. The focus of this study is rare eye disorders, a group of conditions whose clinical...

Incorporating Knowledge-Driven Insights into a Collaborative Filtering Model to Facilitate the Differential Diagnosis of Rare Diseases.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Rare diseases, although individually rare, collectively affect one in ten Americans. Because of their rarity, patients with rare diseases are typically left misdiagnosed or undiagnosed, which leads to a prolonged medical journey. The diagnosis pathwa...

Deep neural models for extracting entities and relationships in the new RDD corpus relating disabilities and rare diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: There is a huge amount of rare diseases, many of which have associated important disabilities. It is paramount to know in advance the evolution of the disease in order to limit and prevent the appearance of disabilities and ...

Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning.

Scientific reports
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of p...

Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers.

Artificial intelligence in medicine
OBJECTIVE: Death certificates are an invaluable source of cancer mortality statistics. However, this value can only be realised if accurate, quantitative data can be extracted from certificates-an aim hampered by both the volume and variable quality ...

Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. Patients with rare diseases are frequently misdiagnosed or undiagnosed which may due to the lack of knowledge and experience of care providers. We...