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Rare Diseases

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An Enhanced Classification Framework for Limited IoHT Time Series Data Using Ensemble Deep Learning and Image Encoding.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent studies have illuminated the potential of harnessing the power of Deep Learning (DL) and the Internet of Health Things (IoHT) to detect a variety of disorders, particularly among patients in the middle to later stages of the disease. The utili...

Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.

Journal of biomedical semantics
INTRODUCTION: Healthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. These knowledge sources are regularly represented as 'linked' resources based on the Resource Description Framewor...

[Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems].

Schmerz (Berlin, Germany)
BACKGROUND: Rare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support...

Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases.

Pharmaceutical medicine
The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a ...

[Rare disease in the age of artificial intelligence.].

Recenti progressi in medicina
INTRODUCTION: The text examines the impact of artificial intelligence (AI) in the context of rare diseases, exploring how patients turn to AI resources for health information, especially in situations where doctor-patient communication is limited. Th...

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa d...

Innovations in Medicine: Exploring ChatGPT's Impact on Rare Disorder Management.

Genes
Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use, ChatGPT holds a prominent position, using an innovative language model develope...

A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.

Scientific reports
To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based...

Navigating the uncommon: challenges in applying evidence-based medicine to rare diseases and the prospects of artificial intelligence solutions.

Medicine, health care, and philosophy
The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow movement towards improved understanding of pathophysiology and treatments compared with more common illnesses. The push towards evidence-base...