Health social network for chronic illness patients
Health social network for chronic illness patients
Healp is a dedicated mobile application aimed at discovering health insights, fostering connections with like-minded individuals, and accessing personalized support.
By creating detailed user profiles, the app enables sharing personal health journeys and connecting with others facing similar challenges. The app incorporates a unique matching system, pairing users with individuals who share similar health conditions. Through various messaging options such as individual chats, community forums, and group discussions, users can seamlessly communicate and engage with one another. Healp also grants access to a comprehensive database of health information, treatments, and tips, curated based on insights from other users. This resource empowers users with the knowledge needed to make informed decisions about their health.
In addition to the mobile app, Healp features a robust web-based admin dashboard. This intuitive tool empowers administrators to efficiently manage users, health topics, and community surveys.
When you have a health condition, it can feel overwhelming. Healp addresses this by tackling two key areas:
1. Creating relatable emotional support community
Healp eases the emotional burden of chronic health conditions by connecting individuals with the same condition. This allows users to find friends who understand their struggles and can offer mentorship and support, reducing feelings of isolation and providing a supportive community.
2. Allowing to discover others' experiences with treatments
Healp solves the problem of finding reliable health information by creating a platform where users can ask questions, compare experiences, and find solutions together. Users can share reviews on drugs, treatments, and remedies, and exchange insights on their effectiveness and impact on health.
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“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”
Joanna Kasprzak, Ph.D. in Bioinformatics, is a specialist in data simulations and algorithms. In Apzumi, she has led over 30 successful Digital Health applications as a Project Manager or Product Owner.
Sebastian Zarzycki, MSCS in Software Engineering, has over 18 years of experience in designing, architecting, implementing and overseeing software. He's involved in all key Apzumi projects.
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Healp is a dedicated mobile application aimed at discovering health insights, fostering connections with like-minded individuals, and accessing personalized support.
By creating detailed user profiles, the app enables sharing personal health journeys and connecting with others facing similar challenges. The app incorporates a unique matching system, pairing users with individuals who share similar health conditions. Through various messaging options such as individual chats, community forums, and group discussions, users can seamlessly communicate and engage with one another. Healp also grants access to a comprehensive database of health information, treatments, and tips, curated based on insights from other users. This resource empowers users with the knowledge needed to make informed decisions about their health.
In addition to the mobile app, Healp features a robust web-based admin dashboard. This intuitive tool empowers administrators to efficiently manage users, health topics, and community surveys.
When you have a health condition, it can feel overwhelming. Healp addresses this by tackling two key areas:
1. Creating relatable emotional support community
Healp eases the emotional burden of chronic health conditions by connecting individuals with the same condition. This allows users to find friends who understand their struggles and can offer mentorship and support, reducing feelings of isolation and providing a supportive community.
2. Allowing to discover others' experiences with treatments
Healp solves the problem of finding reliable health information by creating a platform where users can ask questions, compare experiences, and find solutions together. Users can share reviews on drugs, treatments, and remedies, and exchange insights on their effectiveness and impact on health.
The first step involved converting scanned documents into digital formats using OCR technology. This phase was crucial due to the diverse nature and quality of the scanned documents. Advanced OCR solutions were employed, capable of handling various text formats, handwriting, and even low-quality scans, ensuring high accuracy in digitization.
Once digitized, the documents were categorized into predefined classes such as medical reports, lab tests, and billing documents. This categorization was facilitated by a machine learning model trained on a large dataset of annotated healthcare documents. The model was fine-tuned to recognize and categorize documents accurately, even when the formats and templates varied significantly.
The extraction of key facts from the categorized documents was the next critical step. Using natural language processing (NLP) and machine learning algorithms, the system identified and extracted pertinent information such as patient names, birthdates, addresses, ICD codes, and details of medical procedures. The AI model was trained to understand the context and semantics of the healthcare domain, ensuring a high level of precision in fact retrieval.
The final step involved synthesizing the extracted information into coherent medical summaries and reports. Generative AI models, trained on a vast corpus of medical texts, were employed to generate summaries that were both accurate and easily comprehensible. These summaries provided a consolidated view of the patient's medical history and current claims, significantly aiding in the decision-making process.
