Generative AI tool for images and coloring books

Generative AI tool for images and coloring books

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About

The Problem

Key

Features

AI image generation
Converting images into graphics
Pixel mode
Outline mode
PDF export
Merchandise store

Project

Timeline

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Client

Credentials

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

“Experience in medical Apps is a big advantage of Apzumi for me. The team members are also very helpful with their valuable insight.”

Ajay Kumar
United Kingdom

Reach

Us

Joanna Kasprzak

Chief Operating Officer

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

Chief Technology Officer

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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Back to Case Studies

Generative AI tool for images and coloring books

Category: 
This is some text inside of a div block.
This is some text inside of a div block.

Client

Industry

Market

Engagement

Scope

Team Size

MVP

Partnership

Project description
Project results
About the problem
Project scope
Step 1
Document Digitalization

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.

Step 2
Document Categorization

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.

Step 3
Key Facts Retrieval

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.

Step 4
Medical Summary and Report Generation

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.

Key features
AI image generation
Converting images into graphics
Pixel mode
Outline mode
PDF export
Merchandise store
live chat
with doctor
knowledge
base
rehab
programs
fitbit
integration
analytical
dashboard
HIPAA
compliance
parameters
tracking
Project timeline
Project tech stack
No items found.
Project tool stack

Jira Cloud

Project Management

Confluence Cloud

Project Documentation

Atlassian Cloud

Project Management

Slack

Project Communication

Notion

Project Documentation

Figma

UI/UX Design

Twillio

Video Calls Integration

Google Maps

Geolocation

Gmail

E-mails Integration
Technical description