Bridging the Gap Across Biomarker and AI/M Innovations to Clinical Implications: A White Paper on Challenges and Collaborative Solutions for Chronic Brain Disorders

Abstract

The emergence of artificial intelligence and machine learning (AI/ML), along with novel biomarker platforms for diagnosis, staging and prognosis advances significantly the medical field.On the other hand, it poses considerable challenges regarding their integration into clinical practice and accessibility to patients.Thus, adaptation of the new medical products and advanced technologies into clinical care remains the current hurdle.This editorial discusses the critical barriers hindering the implementation of effective and efficient care opportunities for patients with chronic brain disorders with a specific emphasis on Alzheimer's disease and related dementias (AD/ADRD).Topics examined include the challenges affecting patients, providers, and other stakeholders, including issues related to data standardization, regulatory constraints, and economic obstacles.This paper seeks to foster innovation and collaboration among policymakers, the insurance and pharmaceutical industries, healthcare providers, and innovations developers to bridge the gap between biomarker discoveries and machine learning approaches and their real-world applications.

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