PubMed دسترسی آزاد

Digital Pathology in Dermatology - Current Status, Applications and Perspectives.

استودیوی صوتی مقاله

پخش حرفه‌ای فارسی و انگلیسی

در حال بررسی نسخه‌های صوتی ذخیره‌شده…

صوت تولیدشده با هوش مصنوعی است. برای کاربرد علمی یا درمانی، متن و منبع اصلی را بررسی کنید.
خواندن هوشمند فارسی و انگلیسی در حال آماده‌سازی صداهای مرورگر…
تنظیم صدای طبیعی و سرعت

صداهایی که در نامشان «Natural»، «Neural» یا «Online» دیده می‌شود معمولاً طبیعی‌ترند. انتخاب صدا به صداهای نصب‌شده در ویندوز و مرورگر شما بستگی دارد.

چکیده اصلی

Digital pathology has become an increasingly established component of routine diagnostic practice in recent years. Whole-slide imaging enables the complete digitization of histological slides and allows for primary diagnosis using digital images. This development offers new opportunities for diagnostics, consultations, archiving, education, and quality assurance. In dermatology and dermatopathology, digital pathology is particularly relevant for the evaluation of inflammatory skin diseases, melanocytic lesions, epithelial skin tumors, and immunohistochemical analyses. This article provides an overview of the technical principles of digital pathology, describes workflow integration and implementation in clinical routine, and outlines requirements for quality assurance and validation. Key applications in dermatology as well as advantages and limitations of digital diagnosis are discussed. A dedicated section addresses the role of artificial intelligence as an assistive tool in dermatopathological diagnostics. The aim of this CME article is to provide dermatologists and pathologists with a comprehensive basis for evaluating and applying digital pathology systems in clinical practice and to place current developments into a realistic clinical context.

متن کامل اصلی

نسخه دارای مجوز در منبع علمی در دسترس است.

لینک مستقیم از metadata منبع گرفته شده و در تب جدید باز می‌شود.

باز کردن متن کامل

کلیدواژه‌ها

Artificial intelligenceDermatopathologyDigital pathologyQuality assuranceTelepathologyWhole‐slide imaging
در همین زیرشاخه

مقاله‌های مرتبط

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and enviro…

PubMed2026

Development and Nationwide Multicentre Evaluation of Guideline-Grounded Large Language Model Chatbots to Support Patient Self-Management and Education in Rheumatology.

Patients with rheumatic diseases have persistent information needs that are not fully addressed in routine care. We developed and evaluated guideline-grounded, large language model (LLM) chatbots to support patient self-management and education in rheumatology.Ten disease-specific chatbots based on German guidelines were co-developed and deployed through 13 rheumatology centres and six patient organisations. Chatbot users rated respons…

PubMed2026

Liability and Standard of Care in AI-Driven Psychiatric Practice: European Viewpoint.

AI is increasingly incorporated into psychiatric triage, risk prediction, passive monitoring, clinical documentation, and patient-facing conversational systems. These applications may improve access, continuity, efficiency, and pattern recognition, but they also redistribute epistemic authority and complicate responsibility when harm occurs. European regulation is developed in relation to market access, data governance, risk management…

PubMed2026

Routine laboratory panels classify internal medicine ICD-10 code groups: comparison with frontier large language models and laboratory-only specialist assessment.

INTRODUCTION: Routine laboratory panels are nearly universal, but the panels' joint information is underused. We evaluated contemporaneous classification of International Statistical Classification of Diseases, Tenth Revision (ICD-10) code groups from same-encounter laboratory results. METHODS: We developed 17 eXtreme Gradient Boosting (XGBoost) classifiers in 242 648 adult internal medicine encounters using age, sex, and results from …