AMAI is a competent partner for AI integration
AI in healthcare
Between printing and digitization: Why AI is important now
Clinics, practices and healthcare providers face major organizational and medical challenges: demographic change, shortage of skilled workers, economic pressure.
With AI technologies, AMAI helps automate processes, process medical information faster and organize care more efficiently, always in line with data protection and regulation.
Real Results
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Real Results
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What AI can make a difference in healthcare: More time, more quality, more clarity
Artificial intelligence opens up new ways to relieve medical professionals, make better use of valuable resources and manage patient care in a more targeted manner.
Typical uses for AI in healthcare:
- Automated documentation to relieve doctors and nurses
- Image processing & diagnostic assistance for radiological and pathological evaluations
- Early risk identification through forecasting models and progress forecasts
- Text analysis & medical coding from doctor's letters and case reports
- Process optimization in administration, billing & control of supply
Real Results
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Real Results
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Clear specialization: AMAI as an AI partner for healthcare
As a pure AI consulting and development company, AMAI is fully focused on the development and integration of AI strategies as well as production-ready, explainable and privacy-compliant AI solutions. We bring AI expertise to where it is urgently needed. Our claim: Humans and AI work together for concrete, measurable improvements.
Places of use where AI can develop potential together with our partners:
- Clinics & clinic associations
- Medical care centers
- Health Insurance Companies & Associations of Statutory Health Insurance Physicians
- Provider of practice software & medical technology
Use cases: Examples of how you can use AI in your company
Automated comprehension of findings
NLP analyses doctors' letters and clinic reports for clarity, risks and medical advice for more structured communication with patients.
Automated ICD Ops Coding
Machine learning classifies hospital cases faster, comprehensibly and auditable for billing and quality assurance.
Real-time prioritization and triage
Analysis of patient data enables accurate case prioritization and triage in real time
Genetic analysis and editing
With AI, the effects of gene edits can be predicted that classical computer programs cannot calculate.
Collaborative robot
Cobots are flexible robots that learn by imitating the behavior of human workers. They provide a flexible method of automation.
Medical image analysis
Advanced medical imaging to highlight potentially harmful areas and model potential situations.
Medical device effectiveness analysis
Use AI to better analyze the effectiveness of drugs and medical devices
Predictive maintenance
To prevent malfunctions or poor maintenance from leading to expensive downtime, an algorithm predicts the risk of equipment failure and the need for maintenance.
production planning
With the help of a model, hidden patterns in historical sales data can be identified, such as seasonal demands, the behavior of subsidiaries, or buying behavior when introducing new products. This allows production to be planned accurately.
Inventory forecasting
Use machine learning to take your inventory and supply chain optimization to the next level
Healthcare resource forecast
Predictive models for bed utilization, emergency room figures or staff-intensive services improve planning & shift management.
robotics
Automating manual processes in manufacturing or logistics using advanced robotics
Sorting and reducing waste
AI can be used to minimize the waste of defect-free products and to ensure 100% waste of defective products. It prevents over-disposal of products.
Increasing output through pattern recognition
Identifying patterns (modelling patterns) between input and output of batches and analyzing performance parameters can significantly increase output.
Assisted or automated diagnosis & prescription
Analyzing chronic conditions using laboratory data and other medical data to enable early diagnosis
Improved colonoscopy
According to Leufkens et al. (2012), typical colonoscopy screenings miss 22% - 28% of polyps and 20% - 24% of adenomas. Using machine learning, the live 2D image from colonoscopy can be reconstructed into a 3D model of the large intestine, which highlights segments that require additional coverage.
Our process model: This is how we move your AI initiative forward.
As a pure AI consulting and development company, we focus exclusively on AI projects. Our four-stage process model offers you maximum orientation from strategy to production-ready implementation. You don't have to go through all steps: We start right where you are and reliably bring your AI initiative to the next level.
AI Strategy
Right from the start: Your AI Strategy with substance
Before individual use cases are developed and evaluated, we work with you to define your company's overall AI strategy. In doing so, we define goals, fields of action, governance objectives and long-term development directions. This creates clarity, focus and priorities and forms the basis for all next steps, from use case workshops to implementation.
AI Integration
From code to production systems: We're bringing AI to the streets
With proven components, proven infrastructure and close coordination with your team, we efficiently put your AI solution into productive use. Real transfer of knowledge is taking place continuously.
✔ No prototype without a plan.
✔ No project has no effect.
✔ No effort without results.
Case studies: Successfully implemented AI projects
Real Results
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Real Results
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AMAI — Your Guide to AI Expertise from Strategy to Code.
About AMAI: What sets us apart!
We are not a generalist with an AI connection — we are AI specialists with implementation experience. It is precisely this concentration that brings speed, quality and impact to our customers.
Jürgen Stumpp
Managing Director, AMAI GmbH
Tools & partners
Our areas of expertise
AI use case identification & evaluation
AI business cases & roadmaps
Model development & ML engineering
System integration & productive implementation
Productivity, Scaling & Enablement
Explainability & responsible AI
15
+
years of experience in AI development
50
+
realized AI projects
100
%
specializing in AI projects
