AIMC Topic: Artificial Intelligence

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Image Features of Resting-State Functional Magnetic Resonance Imaging in Evaluating Poor Emotion and Sleep Quality in Patients with Chronic Pain under Artificial Intelligence Algorithm.

Contrast media & molecular imaging
The balanced iterative reducing and clustering using hierarchies (BIRCH) method was adopted to optimize the results of the resting-state functional magnetic resonance imaging (RS-fMRI) to analyze the changes in the brain function of patients with chr...

SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine.

Journal of healthcare engineering
Syndrome differentiation is the most basic diagnostic method in traditional Chinese medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity, and vagueness. Recently, artificial intelligent...

A CNN Model for Cardiac Arrhythmias Classification Based on Individual ECG Signals.

Cardiovascular engineering and technology
PURPOSE: Wearable devices in the scenario of connected home healthcare integrated with artificial intelligence have been an effective alternative to the conventional medical devices. Despite various benefits of wearable electrocardiogram (ECG) device...

Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.

International journal of clinical pharmacy
Background Medication review is time-consuming and not exhaustive in most French hospitals. We routinely use an innovative hybrid decision support system using Artificial Intelligence to prioritize medication review by scoring prescriptions by their ...

[Artificial intelligence and glaucoma: A literature review].

Journal francais d'ophtalmologie
In recent years, research in artificial intelligence (AI) has experienced an unprecedented surge in the field of ophthalmology, in particular glaucoma. The diagnosis and follow-up of glaucoma is complex and relies on a body of clinical evidence and a...

A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients. In an emergency department, automatic detection and...

Technologies bringing young Zebrafish from a niche field to the limelight.

SLAS technology
Fundamental life science and pharmaceutical research are continually striving to provide physiologically relevant context for their biological studies. Zebrafish present an opportunity for high-content screening (HCS) to bring a true in vivo model sy...

Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.

European radiology
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...

Overview on prediction, detection, and classification of atrial fibrillation using wavelets and AI on ECG.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common supraventricular cardiac arrhythmia, resulting in high mortality rates among affected patients. AF occurs as episodes coming from irregular excitations of the ventricles that affect the functionality of the...

Human Activity Recognition via Hybrid Deep Learning Based Model.

Sensors (Basel, Switzerland)
In recent years, Human Activity Recognition (HAR) has become one of the most important research topics in the domains of health and human-machine interaction. Many Artificial intelligence-based models are developed for activity recognition; however, ...