Results

7.7h

saved per week for doctors.

80%

reduction in documentation workload.

2.5x

times more detailed reports compared to manual entries.

The complexity of medical terminology

Developing a highly accurate language model for medical terminology was particularly challenging due to the complexity and specificity of medical terms.

Real-time functionality for seamless workflows

It was essential to ensure the operates in real time to maintain the uninterrupted workflow of practicing physicians.

Secure handling of sensitive patient data

The processing of sensitive patient data also required functioning solutions in order to be able to guarantee the higher requirements in this area at all times.

Our approach

Data-driven innovation: Our data-based solution was developed to significantly increase efficiency in medical documentation.

AI for healthcare: With artificial intelligence, we have automated medical documentation and thus created valuable time for doctors to provide direct patient care.

Language technology for medicine: Our cutting-edge speech technology accurately transcribes and structures medical conversations, ensuring comprehensive and precise documentation.

Industry perspective

30%

of German healthcare CEOs are already leveraging AI solutions to optimise workflows and automate administrative tasks, freeing up more time for patient care.

188bil.

is the projected global market value by 2030 of AI in healthcare, which offers immense potential for innovation and efficiency improvements.

Overview

Project scope

The project included the development of an AI-based solution for automated transcription and documentation of medical conversations. The focus was on the precise recognition of medical terms, the preparation of structured reports and integration into existing practice management systems.

Key Objectives & Deliverables

1

Development of a precise LLM for the recognition of medical terminology.

2

Create a robust natural language processing (NLP) model to extract relevant information from medical conversations

3

Design a user-friendly interface for optimal use.

4

Ensuring data protection and security.

Adiu health is an innovative start-up that specializes in automating medical documentation. With the help of AI, Adiu is revolutionizing the way doctors document their patient treatments through tailor-made summaries.

Health & AI

The healthcare sector is facing a digital transformation in which artificial intelligence is playing an increasingly important role. AI applications have the potential to increase process efficiency, improve the accuracy of diagnoses, and personalise patient care. From medical image processing to drug development, AI opens up new opportunities to meet healthcare challenges.

Lorem ipsum

Every second doctor experiences burnout — the main causes: too much paperwork, bureaucracy and too long working hours.

Medscape Physician Burnout and Depression Report, 2024

Project phases

Stage 1
Preparation & prototyping

Defining the capabilities of the application: Automated transcription and documentation of medical conversations.

Implementation of a minimal prototype: Demonstration of the options for transcribing and summarizing doctor-patient conversations.

Designing an intuitive front end

Stage 2
Implementation & deployment

Deploy to AWS: Hosting a complete solution on AWS

Implementation of an intuitive front end: Building a modern React-based web front end.

Stage 3
Evaluation & improvement

Evaluation: Intensive system and functional testing with a small group of domain experts (doctors).

Improvement: Integration and implementation of feedback from the test group regarding the range of functions and use.

Stage 4
handover

Comprehensive training and knowledge transfer: Documentation and implementation of training courses to ensure seamless takeover and independent registration by the customer.

Long-term partnership: Equip Adiu with the tools and support for continuous improvement while ensuring that Perelyn's expertise is always available.

Stage 1
Preparation & prototyping

Defining the capabilities of the application: Automated transcription and documentation of medical conversations.

Implementation of a minimal prototype: Demonstration of the options for transcribing and summarizing doctor-patient conversations.

Designing an intuitive front end

Stage 2
Implementation & deployment

Deploy to AWS: Hosting a complete solution on AWS

Implementation of an intuitive front end: Building a modern React-based web front end.

Internal productionalization: Rollout to different departments within the company.

Stage 3
Evaluation & improvement

Evaluation: Intensive system and functional testing with a small group of domain experts (doctors).

Improvement: Integration and implementation of feedback from the test group regarding the range of functions and use.

Stage 4
handover

Comprehensive training and knowledge transfer: Documentation and implementation of training courses to ensure seamless takeover and independent registration by the customer.

Long-term partnership: Equip Adiu with the tools and support for continuous improvement while ensuring that Perelyn's expertise is always available.

Which solution are you looking for?

Overview

We have developed an innovative solution that revolutionises medical documentation.
Our software leverages cutting-edge AI technologies to enable precise and efficient automatic transcription of medical conversations — fully compliant with GDPR!

Benefits for companies

The AI-based transcription solution optimizes documentation processes across industries — from healthcare and law to education and finance to media and customer service. It enables efficient protocols, archiving and customer interactions and adapts flexibly to individual requirements.

Technical architecture & integration

Our platform is modular and can be adapted to individual requirements. By using cloud-based technologies, we enable high scalability and can therefore also process large amounts of data.

Adiu

Consultation creation

Transcription

Summarisation

Crystal clear audio recordings via web and mobile

Medical history processing using previous doctors’ insights

Thorough patient analysis

Blazingly fast NVIDIA A10 Tensor Core GPU

Near real time batch processing on EU hosted AWS EC2 machines

Extremely accurate OpenAI Whisper transcriptions

State of the art LLM by Anthropic -Claude 3.5 Sonnet

Serverless Computing with AWS Lambda

Detailed medical documentation

Key Tech

Transcription

AWS Bedrock, Amazon Comprehend, Google VertexAI, Azure Open AI, HuggingFace Transformers, LangChain, LangSmith, LLamaIndex

Summarisation

Anthropic, OpenAI, AWS Bedrock

Modern frontend

React

Data security

AWS Private VPC, all processing and storage is done in the EU.

Cloud

AWS, ECS, CloudFront, MongoDB

Programming languages

Python, TypeScript

Ongoing process

Building Partnerships for Innovation

Adiu Health leverages AI to transform vast amounts of medical guideline literature into knowledge graphs. For the efficient and secure storage and utilisation of these knowledge graphs, Adiu Health relies on Neo4j’s state-of-the-art graph database solution.

By integrating these knowledge graphs with LLMs, Adiu Health enables physicians to perform precise and personalised searches or enhance consultation summaries with automated follow-up checks, such as guideline-based reviews of potential medications or treatment strategies.

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