Introduction
The integration of Artificial Intelligence (AI) into clinical practice is not about replacing physicians but rather augmenting their ability to diagnose, treat, and manage patients effectively.
Case Presentation: Rivka, a 45-Year-Old Woman with Non-Specific Symptoms
Rivka, a 45-year-old woman, presents with fatigue, unexplained weight gain, and intermittent palpitations. While these symptoms are non-specific, they raise concerns for possible metabolic, endocrine, or cardiovascular pathology. A structured diagnostic approach, supported by AI-assisted tools, can help refine the differential diagnosis and optimize patient care.
Clinical Approach and AI Integration
1. Comprehensive Cardiovascular Assessment
Given Rivka’s palpitations and fatigue, an echocardiogram was performed to assess for structural or functional abnormalities. It showed mild left ventricular hypertrophy, an early sign of hypertension-related cardiac remodeling.
To further assess cardiovascular risk, Rivka’s electrocardiogram (ECG) was analyzed which detected subtle QRS voltage changes consistent with early hypertensive heart disease. Recognizing these early markers allowed for timely intervention.
2. Laboratory Evaluation and AI-Driven Pattern Recognition
Routine bloodwork, including a comprehensive metabolic panel and thyroid function tests, was ordered. AI-based laboratory analytics flagged her TSH as borderline elevated, prompting further evaluation with thyroid antibodies, which confirmed Hashimoto’s thyroiditis.
Without AI-supported lab interpretation, these findings may have been considered within normal variation and gone unrecognized until symptoms progressed.
3. Individualized Treatment Planning
With dual diagnoses of subclinical hypothyroidism and early-stage hypertensive heart disease, treatment was tailored accordingly:
- Endocrine Management: Low-dose levothyroxine was initiated based on TSH trends and symptomatology.
- Cardiovascular Protection: A low-dose beta-blocker was prescribed to manage early hypertension and reduce cardiac remodeling risk.
- Lifestyle Modification: The doctor provided personalized dietary and exercise recommendations, reinforcing evidence-based lifestyle interventions.
Discussion: The Role of AI in Clinical Practice
Rivka’s case demonstrates how AI can enhance, not replace, clinical judgment. The physician remains at the center of decision-making, using AI as a tool to:
✅ Improve diagnostic accuracy by detecting early, subtle disease markers.
✅ Identify patterns and risk factors that may not be immediately apparent.
✅ Streamline data interpretation, reducing cognitive overload.
✅ Optimize treatment selection and patient counseling based on real-time analytics.
Conclusion
AI in medicine is a complementary asset, refining the clinician’s ability to detect disease early, guide precise interventions, and improve patient outcomes. By incorporating AI into routine clinical workflows, physicians can make faster, more informed decisions, ultimately delivering higher-quality, patient-centered care.
Dr. Sarah Rosanel is a dedicated concierge physician based in Miami, FL, specializing in personalized healthcare tailored to the unique needs of her patients. With a holistic approach that blends traditional medicine, lifestyle interventions, and functional medicine, she empowers individuals to achieve optimal health and well-being.
As an expert in Concierge Medicine & Cardiology, Dr. Rosanel integrates cutting-edge medical treatments with holistic methodologies, ensuring comprehensive care that goes beyond symptom management to address the root causes of health concerns.
Beyond her medical practice, Dr. Rosanel is a devoted mother to Ariel, Zev, and Shirley, balancing her passion for healing with the joys of family life.
Book your appointment today by texting or calling (646) 467 4368.
Miami, Florida. [email protected]
