From Patient to Problem Solver

How living as both a patient and physician shaped a pathologist’s determination to ask better questions and use AI to solve problems that matter to patients

By
Helen Bristow
September 23, 2026
10 min

The Pathologist

At a Glance

Category	Detail
Condition	Pathology and AI in Medicine
Key Mechanisms	Integration of traditional pathology with programming and AI for enhanced diagnostic capabilities.
Target Population	Patients requiring diagnostic pathology services.
Care Setting	Clinical pathology laboratories and translational science environments.

Key Highlights

Luis Cano's journey from patient to physician highlights the importance of empathy in healthcare.
His experience as a child oncology patient shaped his approach to patient care.
Cano emphasizes the significance of asking the right questions in problem-solving.
He advocates for combining traditional pathology with computational tools to enhance understanding.
Cano's curiosity drives his exploration of AI's potential in pathology.

Guideline-Based Recommendations

Diagnosis

Utilize a combination of traditional pathology methods and AI tools for accurate diagnosis.

Management

Incorporate patient experiences and perspectives into clinical decision-making.

Monitoring & Follow-up

Regularly assess the effectiveness of AI tools in diagnostic processes.

Risks

Be aware of biases in interpretation and ensure questions guiding AI applications are well-defined.

Patient & Prescribing Data

Patients with various pathologies requiring diagnostic evaluation.

Understanding the underlying mechanisms of diseases through pathology can guide treatment decisions.

Clinical Best Practices

Engage in continuous learning and adaptation of new technologies in pathology.
Foster a collaborative environment that values diverse perspectives in problem-solving.