AIMC Topic: Syndrome

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AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...

Predicting disease-gene associations through self-supervised mutual infomax graph convolution network.

Computers in biology and medicine
Illuminating associations between diseases and genes can help reveal the pathogenesis of syndromes and contribute to treatments, but a large number of associations remained unexplored. To identify novel disease-gene associations, many computational m...

A machine learning model to predict the risk of depression in US adults with obstructive sleep apnea hypopnea syndrome: a cross-sectional study.

Frontiers in public health
OBJECTIVE: Depression is very common and harmful in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). It is necessary to screen OSAHS patients for depression early. However, there are no validated tools to assess the likelihood of depr...

Pediatric Psoriasis Associated with Van Wyk Grumbach Syndrome: A case report.

La Tunisie medicale
INTRODUCTION: Psoriasis is a common chronic inflammatory condition, often beginning in childhood in approximately one-third of cases. It can be associated with various other autoimmune diseases such as rheumatoid arthritis, celiac disease, and thyroi...

Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach.

BMC medical informatics and decision making
BACKGROUND: Functional gastrointestinal disorders (FGIDs), as a group of syndromes with no identified structural or pathophysiological biomarkers, are currently classified by Rome criteria based on gastrointestinal symptoms (GI). However, the high ov...

An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.

JAMA network open
IMPORTANCE: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups.

Personalized Intelligent Syndrome Differentiation Guided By TCM Consultation Philosophy.

Journal of healthcare engineering
Traditional Chinese Medicine (TCM) is one of the oldest medical systems in the world, and inquiry is an essential part of TCM diagnosis. The development of artificial intelligence has led to the proposal of several computational TCM diagnostic method...

Robot-Assisted Laparoscopic Calyceo-Pyelostomy for Vascular Compression of the Upper Calyx (Fraley Syndrome).

Urology
Fraley's Syndrome is a rare anatomic vascular malformation described in 1966 where an aberrant crossing vessel compresses the upper infundibulum and leads to upper calyx massive dilation. It is mostly asymptomatic and the diagnosis often missed; howe...

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes.

Alzheimer's research & therapy
IMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context.