AI in Healthcare: On the Path to Clinical Application
OpenAI
Google/DeepMind
Medical AI is still limited in clinical use, mainly covering computer vision and language models, with agent systems playing a smaller role. Real-world deployment requires integrating diverse data types, ensuring data quality, and addressing regulatory and ethical issues, with physicians retaining final responsibility.
Medical AI in 2026 has moved beyond simple demonstrations like image segmentation or diagnosis extraction. Actual clinical deployment requires handling diverse data types—tabular data, electronic health records, medical images, and sequential decisions—each with unique challenges. Data cleaning is critical: missing values, inconsistent encoding, and artifacts must be handled with clinical insight rather than automated statistics. Large language models (LLMs) are best used as digital assistants that generate drafts and structure text, but they can hallucinate or fabricate facts. Retrieval-augmented generation (RAG) grounds LLMs in local knowledge bases, reducing but not eliminating errors. Regulatory bodies like FDA and WHO oversee AI-enabled medical devices, and the EU AI Act classifies many medical AI systems as high-risk. The ultimate decision always rests with the clinical team, making it a 'clinical-team-in-the-loop' rather than just 'doctor-in-the-loop'.
- Сокращения
- NLP = Natural Language Processing — Обработка естественного языка
- LLM = Large Language Model — Большая языковая модель
- RAG = Retrieval-Augmented Generation — Генерация с дополнением извлечением
- CNN = Convolutional Neural Network — Сверточная нейронная сеть
- EHR = Electronic Health Record — Электронная медицинская карта
- CT = Computed Tomography — Компьютерная томография
- MRI = Magnetic Resonance Imaging — Магнитно-резонансная томография
- FDA = Food and Drug Administration — Управление по санитарному надзору за качеством пищевых продуктов и медикаментов
- WHO = World Health Organization — Всемирная организация здравоохранения
- DICOM = Digital Imaging and Communications in Medicine — Цифровая визуализация и коммуникации в медицине
- EDA = Exploratory Data Analysis — Разведочный анализ данных
Source: Habr — хаб ИИ —
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