Key Focus Areas

Financial Barriers

Examining how current reimbursement frameworks lack incentives for adopting AI imaging and management tools in routine bone health care.

Perceived Liability

Addressing concerns about increased legal risks for specialists using AI diagnostics, especially in cases where undetected conditions may lead to adverse outcomes.

Clinical Integration

Identifying workflow challenges that hinder the adoption of AI-driven imaging solutions in busy specialist practices while ensuring alignment with surgical and nonsurgical pain management goals.

Technology Development

Evaluating the feasibility of creating de-identified bone health data sets to support Large Language Model (LLM) analytics and enhance AI algorithm training for future bone health specific clinical applications.

Ethical Use of AI in Bone Health

Promoting responsible AI implementation by ensuring transparency, fairness, and accountability in AI-driven osteoporosis detection and management. This includes addressing biases in AI algorithms, protecting patient privacy, advocating for explainable AI in clinical decision-making, and ensuring AI applications align with ethical medical practices and regulatory standards.