AIMC Topic: Artificial Intelligence

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Introduction of a Pathophysiology-Based Diagnostic Decision Support System and Its Potential Impact on the Use of AI in Healthcare.

Studies in health technology and informatics
Many currently available Diagnostic Decision Support Systems (DDSS) are based on causal condition-symptom relations that exhibit certain shortcomings. Ada's new approach explores the capabilities of DDSS based on pathophysiology, describing a disease...

Maxwell®: An Unsupervised Learning Approach for 5P Medicine.

Studies in health technology and informatics
In the 5P medicine (Personalized, Preventive, Participative, Predictive and Pluri-expert), the general trend is to process data by displacing the barycenter of the information from hospital centered systems to the patient centered ones through his pe...

Improving Adherence to Clinical Pathways Through Natural Language Processing on Electronic Medical Records.

Studies in health technology and informatics
This paper presents a pioneering and practical experience in the development and implementation of a clinical decision support system (CDSS) based on natural language processing (NLP) and artificial intelligence (AI) techniques. Our CDSS notifies pri...

Update on thyroid ultrasound: a narrative review from diagnostic criteria to artificial intelligence techniques.

Chinese medical journal
OBJECTIVE: Ultrasound imaging is well known to play an important role in the detection of thyroid disease, but the management of thyroid ultrasound remains inconsistent. Both standardized diagnostic criteria and new ultrasound technologies are essent...

Clinical Safety Incident Taxonomy Performance on C4.5 Decision Tree and Random Forest.

Studies in health technology and informatics
The paper applies an artificial intelligence centered method to classify 12 clinical safety incident (CSI) classes. The paper aims to establish a taxonomy that classifies the CSI reports into their correct classes automatically and with high accuracy...

Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups.

European journal of orthodontics
OBJECTIVES: To evaluate facial attractiveness of treated cleft patients and controls by artificial intelligence (AI) and to compare these results with panel ratings performed by laypeople, orthodontists, and oral surgeons.