We developed CanceptAI as medical software that can help doctors to save children’s lives. This application optimizes health treatment and real-time symptom monitoring in pediatric oncology. Our AI-algorithms support medication adherence with time reminders to patients, ensuring that children receive their treatments as prescribed. This feature minimizes the risk of missed doses, which can significantly impact treatment effectiveness. Symptom tracking allows doctors to monitor a patient’s condition in real-time. It facilitates timely interventions and adjustments to treatment plans based on the child’s needs. We developed AI-algorithms that create personalized treatment plans based on individual patient data and standardized medical protocols. By analyzing medical lab results, logged symptoms and predictive analytics the system adjusts treatment plans for achieving optimized outcomes. This data-driven approach ensures that each child receives tailored care that evolves as their condition changes. In order to predict potential complications for each child our AI-algorithms analyze patient data and compare it to other similar situations. This predictive capability empowers doctors to make data-driven decisions. We also add the possibility to analyze patients’ lab results directly within the platform. It helps medicines interpret diagnostic information quickly, making adjustments to treatment strategies based on the latest lab data.
Client needs
Our clients needed a solution that effectively managed the medical needs of children with cancer. They wanted to implement personalized treatment plans and real-time monitoring of patient conditions. To reduce the percentage of children dying, medication adherence was a critical concern. So, doctors required effective monitoring of the symptoms.
The stakeholder demanded high-quality data for accurate predictive AI-analytics to ensure data security and regulatory compliance. Given the sensitivity of pediatric patient information added further complexity. Engaging doctors and families in the development process was essential to align the application with clinical needs, making stakeholder collaboration a key aspect of the project.
Discovering business challenges
Pediatric oncology is one of the most emotionally charged fields in healthcare, as it deals with children fighting cancer. For doctors, this means complex treatments, constant adjustments and keeping track of multiple variables. For families, it means anxiety, medication schedules and just the small hope that everything goes by good.
From the first meeting our main aim was to provide life-saving solution, using AI-algorithms to analyze all the possible scientifically-proven data. It helped to propose the treatment plan with further medical adherence prediction adopted to individual lab results of the young patients. So that can empower doctors’ decisions with tremendous data-driven results to minimize any human mistakes.
Development of AI scientific based solutions
At the core of the discovery phase was our understanding of the disjointed healthcare systems and the difficulty of ensuring medication adherence for children. Parents were overwhelmed, and doctors didn’t have real-time access to patient data, meaning vital decisions were delayed. Missing medication doses and late interventions had real consequences, so we needed to provide doctors with instant updates on patient health while simplifying the process for families.
Doctors also expressed their desire for more accurate, real-time data on their patients, especially insights derived from lab results and symptom logs. Families wanted an easy, child-friendly way to ensure that they were sticking to their treatment plans without feeling overwhelmed.
This research made us realize that this wasn’t just about creating a mobile app. We needed to develop solutions that could predict complications, assist doctors in decision-making and most importantly, ensure adherence to treatment plans.
Integration of web and mobile applicatins
We knew that any solution had to be deeply integrated with the existing healthcare infrastructure. Thus, our team identified the most widely used EHR and EMR systems, including Cerner, Epic, Allscripts, and Athenahealth. We needed a solution that allowed interoperability, where CanceptAI could seamlessly sync with these platforms. By adhering to the HL7 FHIR standard, we could ensure that patient records were updated in real-time across different systems, allowing doctors to make data-driven decisions based on the latest information.
Prototype designing
As we moved into the prototype development phase, our focus was on creating a system that was simple enough for children yet powerful enough to be used in clinical settings. The prototypes went through several iterations, with real feedback from healthcare professionals and families. Each iteration brought us closer to a solution that struck the perfect balance between functionality and ease of use. Finally, by integrating AI analytics, we made it possible for pediatric oncologists to predict patient outcomes and adjust treatments dynamically.
The discovery phase wasn’t just about solving a technical problem—it was about understanding the human pain of pediatric oncology and designing a platform that could genuinely improve the quality of life for children and their families. Through constant feedback, research and a user-centered approach, CanceptAI became a powerful tool in the fight against childhood cancer.
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Our Life-saving solution for reliable results
From the beginning our purpose was to create advanced AI-algorithms to analyze extensive, scientifically validated data that is beyond the capacity of the human brain to process. This analysis empowered pediatric oncologists by providing real-time insights into patient conditions and enabling the creation of personalized treatment plans. By integrating AI, we were able to offer predictive models for medical adherence, tailored to the individual lab results of young cancer patients. The result was a tool that not only minimized human error but also enhanced the decision-making process with data-driven accuracy.
At the heart of this development was NestJS, chosen for its scalable backend architecture, which allowed us to build a robust API framework capable of managing large volumes of medical data without compromising performance. The backend integrated with both mobile and web applications, ensuring real-time communication between patients and doctors. The web interface, built using ReactJS, provided doctors with a dynamic dashboard for tracking patient progress, reviewing symptom logs, and making immediate adjustments to treatment plans. The component-based architecture of ReactJS allowed us to deliver a responsive and intuitive interface, which was essential in a clinical environment where efficiency and accuracy are paramount.
Pediatric oncology involves handling numerous variables and the need for timely intervention is critical. Parents are often overwhelmed with managing treatment schedules, while doctors struggle to get real-time access to data. Our solution aimed to bridge these gaps by providing React Native mobile apps for children that offered medication reminders, symptom tracking and real-time updates synced with the doctors’ web app.
To ensure that CanceptAI could integrate seamlessly with existing healthcare infrastructure, we adopted the HL7 FHIR standard, allowing for real-time synchronization with Electronic Health Record (EHR) and Electronic Medical Record (EMR) systems such as Cerner, Epic, and Athenahealth. This interoperability was crucial in providing healthcare professionals with up-to-date patient information, enabling more informed clinical decisions.
One of the core innovations in CanceptAI was its use of TensorFlow and PyTorch to power AI algorithms that could analyze patient data, including lab results, symptoms and medical protocols. These AI models allowed for predictive analytics, which helped doctors anticipate potential complications and adapt treatment plans accordingly. The ability to predict patient outcomes based on a wealth of historical and real-time data transformed the decision-making process, giving doctors a clearer understanding of how to intervene at the right time.
Additionally, the integration of WebSocket technology ensured real-time data synchronization between the mobile app, web app, and backend systems, providing users with the most current patient information. This live updating feature played a vital role in minimizing delays in care and enhancing overall treatment accuracy.
Given the sensitive nature of pediatric health data, maintaining security and regulatory compliance was a top priority. We leveraged AWS to build a secure, HIPAA-compliant cloud infrastructure with advanced encryption for data storage and transmission. Role-based access control was implemented to ensure that only authorized personnel could access sensitive patient information, while regular security audits and compliance checks further guaranteed the platform’s integrity.
In addition to safeguarding patient data, our focus on optimizing the backend architecture ensured the platform could handle large-scale simultaneous data processing, necessary for supporting thousands of clinics across Canada and the USA.
We designed the CanceptAI mobile app with families in mind, making it simple enough for children and caregivers to use, yet sophisticated enough for doctors. The child-friendly interface allowed for easy symptom tracking and medication adherence, while the web app for healthcare professionals featured an extensive dashboard for monitoring real-time data and adjusting treatment plans. The iterative prototype developed with balance between functionality and ease of use. The result was a user-centered design that truly addressed the emotional and medical needs of pediatric oncology patients and their caregivers.
Conclusion
CanceptAI is our valuable contribution for pediatric oncology, combining AI-driven treatment plans with real-time health monitoring. By integrating AI models and ensuring interoperability with major EHR and EMR systems, our platform enables doctors to make informed, data-driven decisions while helping families manage treatment adherence. This two-fold decision-making process improves the quality of care and leads to better outcomes for children with cancer.
healthcare, web platform, telemedicine, toolkit app
