Digital Health & AI Researcher
Rasit Dinc is a digital health and artificial intelligence researcher specializing in clinical AI applications, medical technology innovation, and healthcare transformation. With a focus on evidence-based analysis, Rasit has authored over 693 research articles covering the intersection of artificial intelligence and healthcare, examining regulatory developments from WHO and FDA, analyzing peer-reviewed medical research, and evaluating emerging technologies in digital health.
His work bridges cutting-edge AI research with real-world healthcare implementation, providing insights for healthcare professionals, medical researchers, and technology innovators. Research areas include machine learning in radiology, deep learning for medical imaging analysis, natural language processing in clinical documentation, AI-powered diagnostic systems, digital therapeutics, telemedicine innovations, and clinical decision support technologies.
Recent articles by Rasit Dinc on healthcare AI and digital health technology
Explore how ancient Greek automata and mechanical innovations laid the philosophical and technical foundations for modern health AI, surgical robotics...
Read articlePublished: December 17, 2025
Discover how artificial intelligence is transforming digital health and vascular surgery with advanced diagnostics, predictive analytics, and personal...
Read articlePublished: November 12, 2025
Meta Description: Explore how deep learning algorithms are fundamentally reshaping the radiology workflow in 2025, from triage and image acquisition t...
Read articlePublished: November 11, 2025
The Imperative for Innovation in Breast Cancer Screening Breast cancer remains one of the most common cancers globally, and early detection is the cor...
Read articlePublished: November 9, 2025
The interpretation of Computed Tomography CT scans for lung diseases—including pulmonary nodules, lung cancer, Chronic Obstructive Pulmonary Disease C...
Read articlePublished: November 7, 2025
Magnetic Resonance Imaging MRI is an indispensable tool in modern medicine, offering unparalleled soft-tissue contrast for detailed diagnostic insight...
Read articlePublished: November 5, 2025
Learn why conflict of interest declarations are crucial in digital health and AI research to ensure transparency, trust, and ethical clinical applicat...
Read articlePublished: November 5, 2025
The field of pathology, the cornerstone of disease diagnosis, is undergoing a profound transformation driven by the convergence of digital pathology a...
Read articlePublished: November 3, 2025
The global burden of Diabetic Retinopathy DR, a leading cause of preventable blindness among working-age adults, presents a significant public health ...
Read articlePublished: November 1, 2025
Automated Bone Fracture Detection Using Convolutional Neural Networks: A Digital Health Imperative The rapid evolution of artificial intelligence (AI)...
Read articlePublished: October 30, 2025
The Algorithmic Gaze: Integrating AI into Prenatal Ultrasound for Enhanced Fetal Care The prenatal ultrasound examination stands as a cornerstone of m...
Read articlePublished: October 28, 2025
Explore AI fundamentals, medical imaging applications, and clinical evidence supporting AI's transformative role in healthcare diagnostics and treatme...
Read articlePublished: October 28, 2025
Specialized domains in healthcare AI and digital health technology
Machine learning algorithms in radiology, deep learning for medical imaging, computer vision in pathology, and AI-powered diagnostic tools for clinical practice.
Telemedicine platforms, digital therapeutics, remote patient monitoring, wearable health technology, and healthcare data analytics systems.
FDA medical device regulations, EU AI Act implications, WHO guidance, clinical validation requirements, and post-market surveillance standards.
Emerging technologies in healthcare, AI implementation strategies, clinical workflow integration, and healthcare system digital transformation.
Peer-reviewed study summaries, clinical trial evaluations, evidence-based insights from Nature Medicine, The Lancet Digital Health, JAMA, and BMJ.
AI-powered decision support systems, predictive analytics for population health, precision medicine tools, and real-time clinical assistance technologies.
For inquiries, collaboration opportunities, or feedback on healthcare AI and digital health technology research.