Helia Mokhtari

The integration of artificial intelligence (AI) and natural language processing (NLP) in healthcare has demonstrated transformative potential for disease diagnosis and clinical decision support. This paper presents a comprehensive analysis of current AI and NLP methodologies in healthcare, examining their applications across medical imaging, clinical text analysis, and diagnostic decision support systems. We systematically evaluate performance metrics from 50+ peer-reviewed studies, revealing that AI systems achieve diagnostic accuracies ranging from 88.7% to 96.2% across different medical specialties, often matching or exceeding human expert performance. Our analysis identifies key implementation challenges including data quality, algorithmic transparency, and clinical workflow integration. We propose a framework for responsible AI deployment in healthcare settings and discuss emerging trends in multimodal diagnostic approaches. The findings suggest that while AI and NLP technologies offer significant clinical benefits, successful implementation requires careful attention to technical validation, ethical considerations, and stakeholder engagement.

Amirmohammad Zarif Shahsavan Nejad, Helia Mokhtari, Azita Shirazipour, Soroush Sadeghnejad, Amirmahdi Zarif Verified by AVIS CertificateFIRA World Summit 2026Submitted 17 Sept 2026