The application acts as an advocacy platform for myeloma patients and connects myeloma patients with possible cures. It helps patients navigate their myeloma over the lifetime of there disease, thus helping in the research of new cures. It educates patients about myeloma and enhances their participation in choosing therapeutic options. The application empowers patients to validate the data from different sources for multiple myeloma.

The application is specifically intended for patients with plasma cell dyscrasias and ALS (amyotrophic lateral sclerosis). The data obtained from patients is integrated and processed to derive treatment options along with outcome variables and educative material.

The solution is built for chronic care management along with medical billing to maximize medical reimbursement. It aims to optimize the financial performance of a healthcare organization by ensuring accurate and timely billing, maximizing reimbursements, reducing claim denials, improving overall revenue, and maintaining high standards of patient care.

Developed a skin cancer AI detection app for dermatology, aimed to identify the 3 main skin cancers with over 95% accuracy. Users can track moles for changes. Key features include a user-friendly interface for lesion image capture, AI model integration for analysis, diagnostic feedback, user education, secure data management, validation with medical professionals, basic reporting, and user feedback collection for improvement.

• Cancer diagnosis and treatment information website
• Better collaborate with their treatment teams, to deliver better treatment
• Website offers a personalized education experience to newly diagnosed cancer patients including:
  - Ability to compare FDA-approved treatments by type, stage, and status
  - Ai-powered audio education and curated videos
  - Easy access to financial support from every major pharmaceutical company
• Google map functionality to search top cancer hospitals
• Displaying Ads banner on pages.

The application identifies wound size, shape, area and volume using artificial intelligence (AI) to measure wound circumference, type and progress. It is a platform that allows multiple care facilities to manage wound healing progress rate and wound treatment supplies.

The HIPAA compliant mobile app provides access to real-time wound status and the information is stored for further review from care team. The application provides visual evidence of wound progress and identifies at-risk residents for early intervention.

It also streamlines decision making process and collaboration within care team and is designed for efficient management of wound care supplies.

The application is a preventive and wellness application that acts as an interface through which data flows from remote monitoring devices to a clinic’s EHR system. This platform allows device registration, track patient activities, manage, and mitigate device alerts.  

It can be used to book live face to face as well as remote appointments. This platform also serves as a portal for hospital/home care management. Patients  can  either  self-initiate  disease management remote monitoring program and register  their  devices  or  this  can  be  suggested  by  clinician/hospital  based  on  the  outcome of patient wellness checkup. 

Imaging Systems for Aesthetics and Dermatology. Works in the field of aesthetics and early skin cancer detection, using imaging procedures. Business focus is on the development, image management, archiving, and sale of systems for digital aesthetics, dermatoscopy, and body mapping procedures. We are developing a cloud based solution to integrate new features into the desktop-based medical imaging (SAAS) platform. The application is presently designed to view images and analyse them thereby aiding in the detection of a wide array of dermatological pathologies. Desktop based application is getting migrated to a cloud-based architecture to provide uniform access from various platforms like Macintosh, Microsoft, iPad, and mobile devices.  We also utilize our AI-ML skills in improving image analysis, interoperability, reliance on non-cloud apps, integration of various in-house hardware devices, etc. all factors that will be accommodated while optimizing overall application performance.