About The Project

Initially, dental disease detection and record-keeping were performed manually by dentists through direct checks and individual patient record entries. This led to a shortage of resources for examining large numbers of patients. We observed this issue firsthand during a dental health outreach event for elementary school students in a specific district, where thousands of students needed examinations but only a few dentists were available. To address this, we developed a new innovative product that accelerates the dental check and record-keeping process from 3-5 minutes to just 30 seconds per patient. This acceleration is supported by AI and an automated record system, linked through a web application and QR scanning method to enhance patient mobility without the need for manual data entry.

Goals:

• Speed up the disease detection and medical recording process.
• Achieve high accuracy in disease detection.
• Expand the reach of beneficiaries by making the system accessible.

The User & Audience

• Dentists as the primary checkers of patient diseases.
• Patients as users who can access, add, and update data.

Development Scope

• Development of Artificial Intelligence.
• Website Applications.
• Backend Applications & Backend AI.

Process

Planning Phase:

The process began with an intensive planning stage, where the development team collaborated with dentists and IT experts to identify specific needs and challenges in dental disease detection and record-keeping. During this phase, we conducted a series of discussions, surveys, and brainstorming sessions to ensure that the developed solution met the end-users' needs and could be smoothly integrated into the existing infrastructure.

Prototype Development:

After establishing the needs and technical specifications, we began developing a system prototype. This stage involved creating an AI model capable of identifying various dental diseases from scanned images. This model was trained using a large dataset containing thousands of annotated dental images by professional dentists. Simultaneously, the web development team built a web application for accessing and managing medical records.

Testing and Validation:

The developed prototype was then tested in a controlled environment to evaluate its effectiveness and detection accuracy. This testing involved dentists and patients in real scenarios to ensure that the system was effective and reliable. Feedback received was crucial and used for system iterations and improvements.

Competitors

• Pearl: Offers comprehensive AI-powered dental diagnostics, emphasizing FDA-approved technologies for a broad range of detection capabilities.
• Denti.AI: Focuses on automating pathology detection and charting, notable for its industry-first FDA clearance for panoramic image disease detection.
• VideaHealth: Utilizes AI for early disease detection to enhance diagnostic accuracy and patient care, endorsed by leading dental support organizations in the U.S.
• Overjet: Specializes in detailed imaging analysis and orthodontic assessment, supporting clinical decision-making with extensive AI-driven data analysis.

SWOT Analysis

Strengths

• Localized Focus: "Senyumin" may emphasize local understanding and customization tailored to Indonesian healthcare practices, making it highly relevant for its primary audience.
• Integration with Public Health Services: By collaborating with public healthcare facilities like Puskesmas, "Senyumin" ensures broad accessibility and could potentially receive government support, enhancing its credibility and reach.

Weaknesses

• Resource Limitations: As a new entrant, "Senyumin" might face challenges in resources and funding compared to well-established competitors who already have significant investments and market penetration.
• Brand Recognition: Competitors with international presence and multiple regulatory approvals (like FDA clearance) might overshadow "Senyumin" in terms of brand trust and recognition globally.

Opportunities

• Government and Public Sector Partnerships: By enhancing partnerships with local government and educational institutions for public health initiatives, "Senyumin" can leverage public funding and infrastructure to expand its user base.
• Customization for Local Needs: Developing features that cater specifically to the Indonesian demographic and healthcare challenges could differentiate "Senyumin" from competitors focused on Western markets.

Threats

• Technological Advancements by Competitors: Companies like Pearl and Overjet are leading with advanced AI technologies and have substantial funding to accelerate innovation, which could outpace "Senyumin's" development.
• Regulatory Challenges: Navigating the complex regulatory environment in healthcare can be slower for newer companies, potentially delaying market entry or expansion.