Target Participant Profile: An all-women cohort comprising multi-disciplinary experts:

• AI/ML Engineers: To develop and train the core predictive models.

• Software Developers (Backend/Frontend): To build the functional prototype and user interface for the Care Template.

• Healthcare Professionals (Gynecologists, Oncologists, Nurses, Public Health Specialists): To ensure clinical accuracy, guideline adherence, and user-centricity.

• Finance & Supply Chain Experts: To design and integrate the cost estimation and inventory tracking modules.

• Track 1: Cervical Cancer Risk Prediction & Care Coordination

  1. Prediction Engine: An AI model that stratifies a patient's risk for cervical cancer.

  2. Personalized Scheduling: Automatically recommends screening schedules (e.g., Pap smear, HPV test) based on individual risk profiles and Kenyan national guidelines.

  3. Inventory Integration: Tracks the real-time availability of essential screening and diagnostic tools (e.g., HPV test kits, colposcopes, biopsy supplies) at linked health facilities.

  4. Financial Transparency: Provides patients and providers with an estimated cost for the recommended diagnostic and treatment pathway, and connects patients to potential financing options.

  5. Challenge: Develop an AI-powered system that analyzes patient risk factors (e.g., demographic data, lifestyle, clinical history, HPV status) to predict cervical cancer risk and generate an optimal, evidence-based care pathway.

  6. Required Features:

• Track 2: Ovarian Cyst Growth & Treatment Prediction

  1. Prediction Engine: An AI model that uses patient data (e.g., cyst size/type from ultrasound results, hormonal levels, symptoms) to predict cyst behavior (e.g., likelihood of growth, resolution, or malignancy).

  2. Clinical Decision Support: Recommends a management plan (e.g., watchful waiting, medication, surgical intervention) based on the prediction and aligned with established clinical guidelines.

  3. Inventory Integration: Tracks the real-time availability of necessary resources, such as specific medications or surgical tools required for the recommended treatment plan.

  4. Financial Transparency: Generates clear cost estimations for the proposed management or treatment plan and provides information on financing options.

• Challenge: Develop a predictive model that helps clinicians assess the potential progression of ovarian cysts, suggest appropriate management plans, and integrate corresponding inventory and financial data.

• Required Features: