Deep Learning for Early Diagnosis of Neurodegenerative Diseases: A Review
Conducted a comprehensive review of deep learning approaches for the early diagnosis of neurodegenerative disorders, focusing on multimodal learning, medical imaging, and predictive healthcare systems. The paper explores recent advances in CNNs, transformers, and hybrid architectures for improving early-stage detection accuracy and clinical interpretability.
Research Paper
AI in healthcare
Project Overview
Under Review | Springer
Focus Areas
Healthcare AI · Deep Learning · Medical Imaging · Multimodal Learning · Explainable AI · Neurodegenerative Disease Analysis
Conducted a comprehensive research review on deep learning approaches for early-stage neurodegenerative disease diagnosis, focusing on multimodal AI systems, medical imaging architectures, and predictive healthcare intelligence. Traditional diagnostic workflows often struggle with early detection and interpretability, so the review explored how modern deep learning frameworks improve diagnostic accuracy, clinical reliability, and decision-support capabilities across healthcare applications.
Research Scope
Analyzed recent advancements in AI-driven healthcare systems by comparing deep learning architectures, multimodal diagnostic pipelines, medical datasets, and explainability techniques used in neurodegenerative disease prediction and early screening research.
Key Contributions
Reviewed CNNs, transformers, hybrid architectures, and multimodal deep learning frameworks for neurodegenerative disease diagnosis
Analyzed the role of medical imaging, speech analysis, gait signals, and biomarker-driven prediction systems in early-stage diagnostic workflows
Compared evaluation metrics, interpretability techniques, and deployment challenges across recent healthcare AI research studies
Investigated limitations including dataset imbalance, model generalization, clinical reliability, and real-world deployment constraints
Explored emerging trends in explainable AI, multimodal learning, and predictive healthcare intelligence systems
Structured findings into a comparative literature framework highlighting strengths, weaknesses, and future directions for healthcare AI research
Outcome
The review highlights the growing impact of deep learning and multimodal AI systems in enabling earlier and more accurate neurodegenerative disease diagnosis. It provides a consolidated understanding of current research directions, explainability strategies, deployment challenges, and emerging trends shaping next-generation healthcare AI systems.
Tech Stack
Deep Learning · Healthcare AI · Medical Imaging · Multimodal Learning · Research Analysis · Explainable AI · Scientific Literature Review · Predictive Healthcare Systems
