Custom Telemedicine Software Development Company in Australia

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.

In auto, case creates each referral is matched with the existing patient in the system on the basis of matching criteria system sets the Referral Status, and here the possible referral status. 
Match note found – If no referral found any match with the existing system, in this case system converts that referral into new patients and assigns a case Id to this referral. 
Review Matches – This status is set when there are multiple matches for a referral, in this case, a manual process happens, in this process user selects particular patients and links that patient to this referral. 
The new case created – When a referral is converted to a patient and gets a case id then the referral’s status becomes a new case created. 

Features:
Auto case creation is a technique when a referral is received in the form of an XML file, then this file gets parsed in our product and the information resides in xml files gets saved in the database in sections like Referral Basic Info, Address Info, Diagnosis Info. 

Custom Apparel & Uniform Retail Marketplace, a leading supplier of uniforms and workwear in Australia, sought to enhance its online presence by developing a comprehensive e-commerce platform. The objective was to create a user-friendly website that showcases their extensive product range, facilitates online purchases, and provides detailed information on their offerings. The platform needed to cater to various industries, including corporate, hospitality, healthcare, and sports sectors.
The website was designed to:

• Present a vast array of uniform products with detailed descriptions and high-quality images.
• Enable seamless online purchasing with secure payment gateways.
• Provide information on bulk buying options and customization services.
• Offer an intuitive navigation system for users to easily find products by category.
• Ensure a responsive design for optimal viewing on various devices.

The .NET Core application acts as middleware in this scenario, facilitating the exchange of data between the CCMG EMR (Electronic Medical Records) system and other systems. The middleware retrieves patient data from the CCMG EMR system, which likely includes various medical records and information.

Additionally, middleware handles HL7 lab requests, (Incoming) process consists of lab data files fetching from the lab’s FTP server and save on CCMG FTP server and for (Outgoing) process, patient data from the database created in the form of HL7 ORU message then transfer to client i.e. ftp, post. Implemented process of uploading CCDA to FTP server using PHI direct.

The app uses a BLE device connection as a trigger to start a background task (tracking a user's location). As long as a continuous connection with the BLE device is maintained, the app runs a background task and it stops this task when the BLE connection is terminated. 

The primary objective of the compliance process automation platform is to enhance the operational efficiency of the energy company's Energy Saving Certificate (ESC) process. This will be achieved by automating the collection, validation, and reporting of energy savings data related to lighting, air conditioning, heat pumps, and batteries. The platform aims to reduce manual processing time, minimize errors, and ensure compliance with regulatory requirements, ultimately leading to improved accuracy in reporting and increased energy efficiency.