Related services

• AI Algorithm in Medical Robotics

  Politecnico Di Milano (POLIMI)

  Providing expertise in the field of medical robotics (medical imaging for surgical planning, virtual reality, extended reality) to be eventually tailored to specific projects: 1) Definition of applications objectives 2) Data collection, data curation and bias evaluation 3) Preprocessing and optimization of feature extractions 4) Selection of suitable machine learning models, model training and testing 5) External validation 6) Interpretations of models (XAI algorithm applications and development) Keywords: AI, algorithm development, AI testing and validation, Medical Imaging for Surgical Planning, Virtual Reality, Extended Reality

  View service →
• AI algorithms development and improvement

  Fondazione Bruno Kessler (FBK)

  This service covers all key aspects of development and deployment of AI solutions, based on shallow machine learning or deep learning). State-of-the-art pipelines are generated/improved leveraging on various technonolgies or solutions such as: data encoding, management of missing data, data augmentation and syntetic data generation, model selection and optimisation, hyperparameters tuning, fine-tuning, data shift and transfer learning, reproducibility and explainability. Keywords: Biomedical data Analysis, Deep Learning, CNN, Machine Learning, Image Analysis, Synthetic Data Generation

  View service →
• AI and Optolectronics Prototype Optimization

  Multitel (MULTITEL)

  Design, Optimization and Small Series Production of Prototypes: The MULTITEL team excels in creating bespoke prototypes and limited series, demonstrating the potential of AI and optoelectronics applications in various domains.

  View service →
• AI cybersecurity evaluation

  Laboratoire National De Metrologie Et D'Essais (LNE)

  Evaluation of the AI system regarding its robustness against cybersecurity issues ( risk assessment, secure Data, access Control and Authentication, etc …) This will include the design of test protocols, the realization of tests, the analysis of results and production of a test reports.

  View service →
• AI Imaging Lab: Development & Validation of Segmentation and Detection Models

  Karolinska Institutet (KI)

  ## Overview This service supports SMEs and researchers in developing, training, and validating AI models for medical imaging applications. Hosted at SMAILE, Karolinska Institutet, it covers segmentation, detection, and classification tasks using CT, MRI, nuclear images, multimodal images, ultrasound, histology, and microscopic images. The pipeline includes data curation, evaluation of labeling strategy, model selection and training, evaluation metric selection, and model performance benchmarking. We provide expertise and support in: - AI model training and optimization for medical imaging - Validation using clinical datasets and standard metrics (using publicly available datasets, datasets available through data agreements, and internal datasets at KI, depending on the case) - Clinical Relevance and Comparison with the state of the art in research and clinical practice - Imaging biomarkers studies for diagnosis, prognosis, and prediction applications ### How can the service help you? The service ensures your imaging AI model performs reliably and is aligned with clinical expectations. Whether you’re entering the pre-clinical testing phase or seeking validation to secure investment or regulatory approval, this service equips you with a rigorous evaluation and feedback report. ### How the service will be delivered? Available both virtually and physically. Imaging data can be reviewed remotely through a secure data transfer process. On-site collaboration is also possible for sensitive datasets or model development, evaluation, and validation. A typical project takes 4–6 weeks. --- ## Additional information ### Provider description SMAILE is the digital health core facility at Karolinska Institute. It offers interdisciplinary support in AI for medical imaging, data analytics, and system validation, partnering with leading institutions under the Swedish TEF-Health node. ### Technical description The imaging model pipeline is extensively validated by using a curated benchmark set and standard evaluation frameworks such as well-established quantification metrics for object detection, image segmentation, and classification tasks.. Annotation quality is reviewed, and model performance is benchmarked against open or reference models. Standard medical image processing tools such as PyDicom, ANTs, and ITK, as well as community-driven open-sourced frameworks such as MONAI, are the core components of our designed pipelines. ### Service customization The service can focus on either model development, evaluation, or both. Datasets can be anonymized and securely shared, or analysis can be conducted in a local sandboxed environment.

  View service →
• AI improvement and development

  RISE Research Institutes Of Sweden

  Method description: Develop and improve AI algorithms utilizing Deep Learning paradigms within Computer Vision, Data Analysis and Natural Language Processing. The service can include suggestions of applications and highlight strengths, weaknesses, or software development. The service is customized according to the SME's needs. Pre-requisites for the service are the analysis of data availability, data-readiness level and customer needs. Method reference: To be refined depending on the type of task, and in dialog with the customer. The Center for Applied AI at RISE carries out cutting-edge research in AI, connects expertise and applications within RISE, and explores a wide range of innovative applications with industry and the public sector. Applied AI Centre at RISE helps companies and government agencies to see more potential in the technology, use it more wisely and develop it faster. Keywords: Trustworthy AI, Federated learning, Data Science, AI, Deep Learning, Natural language processing, Computer Vision, Machine Learning

  View service →