AIMedLab.proAI Research in Medicine
AI research partner for medicine

We turn medical research questions into working AI solutions

AIMedLab.pro is a team of AI specialists working with pharmaceutical companies, healthcare institutions and research groups. We study your task and data, then design, build and validate the AI solution that your study needs.

  • Pharma & Biotech
  • Hospitals & Clinics
  • Academic & Research Teams
ImagingCT · MRI · X-ray · pathology
Clinical textnotes · reports · literature
Moleculescompounds · targets · ADMET
SignalsECG · EEG · wearables
Omicsgenomics · transcriptomics · proteomics
How it works

From your research question to a validated AI solution

We do not sell ready-made products. Each solution is designed for one specific study.

  1. 01

    Understand the research question

    We meet your clinicians or scientists, study the hypothesis, endpoints, data sources and constraints, and check whether AI is the right tool at all.

  2. 02

    Data audit & study design

    We assess data quality, volume and labelling, agree on a validation strategy and success metrics, and plan de-identification and access.

  3. 03

    Model development

    We prepare the data, build baselines and iterate on models, showing you interim results at every stage. No black boxes.

  4. 04

    Validation & interpretation

    We validate on held-out and external data, check calibration, bias and explainability, and perform the statistical analysis your reviewers will expect.

  5. 05

    Delivery & support

    You receive a working solution, documented code, a technical report and support for publication, deployment or regulatory submission.

Why AIMedLab.pro

AI engineering held to the standards of medical science

Medical AI often fails when it is built like a generic IT project. We combine machine-learning engineering with the discipline of clinical research: careful validation, honest metrics and respect for patient data.

How we ensure quality

Patient data stays protected

De-identification, minimal data access, encrypted transfer, and on-premises deployment inside your infrastructure when required. Our processes follow GDPR and HIPAA principles.

Scientific rigour

Pre-agreed metrics, proper train/validation/test splits, external validation where possible, and reporting aligned with TRIPOD-AI, CONSORT-AI and similar guidelines.

Explainable by design

Clinicians need to understand why a model makes a prediction. We provide feature attributions, saliency maps and error analysis, not just a single accuracy number.

Regulatory-aware engineering

If a research model could later become a product, we document data lineage, versioning and testing to support a future quality-management and regulatory process.

What you receive

Results you can use, publish and own

Working AI model

Trained, versioned and tested, ready for your environment.

Reproducible pipeline

Clean, documented source code. You own all of it.

Technical & statistical report

Methods, metrics, validation results and limitations.

Publication support

Figures, tables and methods text for your manuscript or grant.

Deployment

On-premises, private cloud or integration into existing systems.

Knowledge transfer

Workshops so your team can maintain and extend the solution.

FAQ

Frequently asked questions

Who are your typical clients?

Pharmaceutical and biotech companies, hospitals and clinics, and academic research groups that have a specific medical research question and the data to explore it, but either no in-house AI team or a team that needs extra capacity.

We are not sure our data is good enough for AI. Can you help?

Yes. Most projects start with a data audit. We assess volume, quality and labelling and tell you honestly what is realistic. Sometimes the right answer is a simpler statistical method, and we will say so.

How do you handle patient data and confidentiality?

We work with de-identified data whenever possible, sign NDAs and data processing agreements, and can work entirely inside your infrastructure so that no data leaves your organisation.

Who owns the results and the code?

You do. Models, source code and results are transferred to you. By agreement, we can co-author publications where our methodological contribution warrants it.

Are your solutions certified medical devices?

No. We build research-grade AI solutions. If your goal is a certified product, we design the work so it can feed into your quality-management and regulatory process, and we document it accordingly.

How long does a typical project take?

A feasibility study usually takes 3–6 weeks. A full research project typically takes 2–6 months, depending on data availability and validation requirements.

Is the first consultation free?

Yes. Tell us about your research question and we will come back with an initial assessment and a proposed approach.

Have a research question?

Tell us about your study, data and goals. We will reply with an initial assessment and a proposed approach. The first consultation is free.