Journal of the American Medical Informatics Association : JAMIA
39998911
OBJECTIVES: This study assesses the abilities of 2 large language models (LLMs), GPT-4 and BioMistral 7B, in responding to patient queries, particularly concerning rare diseases, and compares their performance with that of physicians.
Rare diseases affect 1-in-10 people in the United States and despite increased genetic testing, up to half never receive a diagnosis. Even when using advanced genome sequencing platforms to discover variants, if there is no connection between the var...
International journal of computer assisted radiology and surgery
39739290
PURPOSE: This study explores the use of deep generative models to create synthetic ultrasound images for the detection of hemarthrosis in hemophilia patients. Addressing the challenge of sparse datasets in rare disease diagnostics, the study aims to ...
BACKGROUND: Rare diseases affect millions worldwide but sometimes face limited research focus individually due to low prevalence. Many rare diseases do not have specific International Classification of Diseases, Ninth Edition (ICD-9) and Tenth Editio...
Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment....
Rare diseases impose a significant burden on affected individuals, caregivers, and healthcare systems worldwide. Developing effective therapeutics for these small patient populations presents substantial challenges. Antisense oligonucleotides (ASOs) ...
Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health ...
BMC medical informatics and decision making
39910609
BACKGROUND: Virtual Gene Panels (VGP) comprising disease-associated causal genes are utilized in the diagnosis of rare genetic diseases to evaluate candidate genes identified by whole-genome and whole-exome sequencing. VGPs generated by the PanelApp ...
BACKGROUND: Use of artificial intelligence (AI) in rare diseases has grown rapidly in recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify and analyse large amounts ...
Artificial intelligence applications in oncology imaging often struggle with diagnosing rare tumors. We identify significant gaps in detecting uncommon thyroid cancer types with ultrasound, where scarce data leads to frequent misdiagnosis. Traditiona...