In this simulated navigation system, GenAI is used to predict disease trajectories in patient cases synthesized from real clinical case studies. The following patient examples highlight the potential benefits of applying GenAI after each doctor visit to monitor healthcare decisions by comparing the patient's actual care to the high standards of predictive care identified by GenAI. Such AI-assisted monitoring by navigators can reveal potential gaps in care, alerting patients to take action and engage in shared decision-making with their doctors to achieve timely, accurate diagnoses and personalized treatment.
AI could predict breast cancer early, but the patient declined follow-up, losing the opportunity for early diagnosis and treatment for 5 years.
AI can predict lung cancer in young patients and encourage them to follow up for timely diagnosis and treatment.
Although rare, NPC can occur at a very young age. Timely screening and diagnostic tests are critical for early detection and treatment.
AI can predict colorectal cancer before surgery, enabling early detection and treatment.
AI can predict liver cancer and provide personalized patient education to encourage early treatment planning and preparation for potential post-operative complications.
AI can predict familial pancreatic cancer and provide personalized patient education regarding genetic testing for familial pancreatic cancer.
Predicting early-stage prostate cancer requires monitoring PSA levels and taking additional tests such as the Digital Rectal Exam (DRE), PCA3, and 4Kscore, since there is no single highly specific screening method yet.
AI can predict DLB early, enabling the patient to discuss treatment options with doctors at an earlier stage.
AI can predict DLB and identify gaps in the patient's medications, enabling them to consult doctors about more comprehensive treatment plans.
AI can predict CJD after lab tests, enabling early initiation of treatment.
AI can predict CJD following clinical exams, enabling early treatment.