Comprehensive glossary of artificial intelligence and healthcare terminology.
A set of mathematical rules or instructions that a computer follows to solve a problem or complete a task. In healthcare AI, algorithms analyze patient data, identify patterns, and generate predictions or recommendations to support clinical decision-making.
Technology enabling computers to perform tasks typically requiring human intelligence, including visual perception, speech recognition, decision-making, and language translation. Healthcare AI applications include diagnostic imaging analysis, treatment planning, patient monitoring, and administrative automation.
Software that analyzes patient data and provides evidence-based recommendations to healthcare professionals. AI-powered CDSS systems process electronic health records, medical literature, and treatment guidelines to suggest diagnostic possibilities, treatment options, and preventive measures tailored to individual patients.
AI technology enabling computers to interpret and understand visual information from images or videos. In healthcare, computer vision analyzes medical imaging (X-rays, CT scans, MRIs) to detect abnormalities, measure anatomical structures, and guide surgical procedures with accuracy comparable to human specialists.
Advanced machine learning technique using neural networks with multiple layers to learn complex patterns from large datasets. Healthcare applications include medical image analysis, drug discovery, genomic medicine, and predictive modeling for patient outcomes, achieving performance levels matching or exceeding human experts in specific tasks.
AI approach where computers learn from data without explicit programming, identifying patterns and making predictions based on examples. Healthcare machine learning analyzes patient records, predicts disease risks, recommends treatments, and optimizes hospital operations through continuous learning from clinical outcomes and operational data.
AI technology enabling computers to understand, interpret, and generate human language. Healthcare NLP extracts information from clinical notes, research literature, and patient communications, enabling automated documentation, medical coding, literature review, and chatbot-based patient interactions for health information and support.
Computational model inspired by biological neural networks in the human brain, consisting of interconnected nodes (neurons) that process information. Healthcare neural networks analyze complex medical data, recognizing patterns in images, predicting patient outcomes, and supporting diagnostic decisions through hierarchical information processing.
Using historical data and machine learning to forecast future events or outcomes. Healthcare predictive analytics anticipates patient deterioration, hospital readmission risk, disease progression, and resource needs, enabling proactive interventions and optimized planning before problems occur.
Healthcare approach tailoring medical treatment to individual patient characteristics including genetics, environment, and lifestyle. AI-powered precision medicine analyzes genomic data, biomarkers, and clinical information to recommend personalized therapies, predict treatment responses, and optimize medication dosages for each patient's unique biology.
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