AI Medical Compendium Topic:
Predictive Value of Tests

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Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma.

Virchows Archiv : an international journal of pathology
In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slide...

Deep Learning-Based Approach for the Diagnosis of Moyamoya Disease.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Moyamoya disease is a unique cerebrovascular disorder that is characterized by chronic bilateral stenosis of the internal carotid arteries and by the formation of an abnormal vascular network called moyamoya vessels. In this stury, the au...

Primary Prevention Trial Designs Using Coronary Imaging: A National Heart, Lung, and Blood Institute Workshop.

JACC. Cardiovascular imaging
Coronary artery calcium (CAC) is considered a useful test for enhancing risk assessment in the primary prevention setting. Clinical trials are under consideration. The National Heart, Lung, and Blood Institute convened a multidisciplinary working gro...

Machine Learning-Based MRI Texture Analysis to Predict the Histologic Grade of Oral Squamous Cell Carcinoma.

AJR. American journal of roentgenology
This study aimed to explore the performance of machine learning (ML)-based MRI texture analysis in discriminating between well-differentiated (WD) oral squamous cell carcinoma (OSCC) and moderately or poorly differentiated OSCC. The study enrolled ...

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...

Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: The widespread use of electronic patient-generated health data has led to unprecedented opportunities for automated extraction of clinical features from free-text medical notes. However, processing this rich resource of data for clinical ...

Fuzzy partitioning of clinical data for DMT2 patients.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
The present study represents an original approach to data interpretation of clinical data for patients with diagnosis diabetes mellitus type 2 (DMT2) using fuzzy clustering as a tool for intelligent data analysis. Fuzzy clustering is often used in cl...

Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalized treatment strategies for AD is challenging, given the apparent unpredictability and large variation in AD symptoms ...