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

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• 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

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• AI and Optolectronics Prototype Optimization

  Multitel (MULTITEL)

  ###Overview This service supports healthcare SMEs in the design, development and optimization of AI and/or optoelectronic prototypes, from an initial proof of concept to a more mature, integrated and functional solution adapted to the intended application. Multitel can work on software-based AI prototypes, including the integration and optimization of AI models and data-processing pipelines, as well as prototypes combining AI with sensing, optoelectronics, electronics or embedded systems. Depending on the customer’s needs, the work can address AI performance, software integration, hardware/software integration, sensing and optical components, embedded implementation or overall system performance. The service can also prepare prototypes for subsequent testing, validation, demonstration or further product development. ### How can the service help you? The service is intended for SMEs and technology developers that have an initial proof of concept or prototype and need specialized engineering expertise to transform it into a more mature, functional and application-oriented solution. The prototype can be software-based, such as an AI prototype, or combine AI with hardware, optoelectronics, sensing, electronics or embedded systems. **Before the service**, the customer may have a first AI proof of concept that needs to be transformed into a more robust and integrated prototype, or a hardware-based prototype whose sensing, processing, AI or system components still require integration and optimization. Multitel brings together expertise in machine learning and deep learning, computer vision, multimodal data analysis and signal processing, as well as optoelectronics, sensing and embedded systems when these technologies are required by the application. The service can therefore address either an AI-focused prototype or a multidisciplinary prototype combining software and hardware technologies. **After the service**, the customer receives a more mature and optimized prototype addressing the agreed technical objectives. Depending on the agreed scope, the prototype can support subsequent technical testing, validation, demonstration or further product development, and a limited number of prototype units may also be produced. ### How will the service be delivered? The service starts once the initial objectives, scope and expected outcomes have been agreed with the customer during the quotation phase. Multitel first reviews the existing proof of concept or prototype, available technical information and the main development or optimization objectives. When needed, the technical requirements and target prototype specifications are further refined with the customer at the beginning of the service. Based on the agreed scope, Multitel performs the required development, integration and optimization activities. For an AI/software prototype, these may include AI and data-processing development, software integration, implementation and iterative testing. For multidisciplinary prototypes, additional activities may include optoelectronic or sensing development, embedded implementation, hardware/software integration, prototype assembly and testing. Intermediate results or prototype versions are reviewed with the customer when relevant, and the solution is iteratively refined against the agreed objectives. The service is mainly carried out by Multitel’s technical experts. Medical or clinical expertise is not systematically required, but involvement of the customer’s medical experts or other domain specialists may be necessary when clinical requirements, intended use or application-specific criteria need to be defined or assessed. Any such requirement is identified when defining the scope of the service. Software and AI development activities can be carried out at Multitel and discussed with the customer remotely. Activities requiring specialized equipment, prototype assembly, optoelectronic integration or laboratory testing are carried out at Multitel’s facilities in Belgium. The customer does not need to be located in Belgium, but physical prototypes, components or other necessary equipment may need to be provided to Multitel when required by the project. The execution time depends on the maturity and complexity of the initial prototype, the development and integration activities required, component availability and the number of iterative development and testing cycles. The expected execution time is therefore defined during the quotation phase according to the agreed scope. At the end of the service, Multitel delivers the developed or optimized prototype and the associated technical results. Where included in the agreed scope, a limited number of prototype units may also be produced. ###Use cases/examples **Example 1 – Integration of AI and optical sensing into a healthcare prototype** An SME has demonstrated the feasibility of an optical sensing concept but its current proof of concept consists of separate sensing, acquisition and processing components. Multitel supports the integration of the optical sensing system, electronics, signal processing and AI components into a more compact and functional prototype. The prototype is iteratively tested and optimized according to the application requirements. **Outcome**: an integrated prototype demonstrating the complete sensing and processing chain and suitable for subsequent technical testing and validation. **Example 2 – Optimization of an existing AI-enabled prototype** An SME has developed a first functional prototype combining sensors and AI but needs to improve its integration and performance before proceeding to the next product-development stage. Multitel reviews the system architecture and identified limitations and optimizes selected hardware, embedded processing, signal-processing and AI components. **Outcome**: an optimized prototype with improved system integration and performance, together with technical results supporting subsequent validation and product development.

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• 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.

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• 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.

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• AI Model Development and Improvement

  Multitel (MULTITEL)

  ### Overview This service supports the development and improvement of customized AI models for healthcare applications, from early-stage concepts to existing solutions requiring further optimization. Multitel develops AI components for medical imaging, time-series and sequential data, multimodal data and other application-specific inputs. Depending on the customer’s needs, the work can focus on improving accuracy, robustness, processing speed, explainability, uncertainty estimation or functionality. The service combines expertise in machine learning, deep learning, computer vision, multimodal analysis and signal processing, while keeping clinical relevance, validation, traceability and integration into the medical-device development lifecycle in mind. ### How can the service help you? The service is intended for SMEs and technology developers that need specialized AI expertise to transform healthcare data into a usable AI component or improve an existing solution. Before the service, the customer may have a clinical or technical objective and available data but no suitable AI model, or may already have a model whose accuracy, robustness, explainability, processing speed or functionality needs improvement. Multitel brings expertise in machine learning and deep learning, computer vision, multimodal data analysis, predictive and sequential modelling, signal processing and Trustworthy AI. Depending on the use case, this expertise can be used to select an appropriate modelling approach, develop a new AI component, improve an existing model, or make the solution more suitable for subsequent validation and integration. After the service, the customer receives a developed or improved AI model addressing the agreed objectives, together with documented technical results supporting the next development and validation steps. ### How will the service be delivered? The service starts once the objectives, scope, available data and expected outcomes have been agreed with the customer during the quotation phase. Depending on the agreed scope, Multitel analyses the provided data and, where applicable, the existing AI model. An appropriate modelling and development approach is then implemented, followed by iterative development, testing and evaluation against the agreed objectives. Intermediate results are reviewed with the customer when relevant, allowing the development to be adjusted within the agreed scope. At the end of the service, the developed or improved AI model and the associated technical results are delivered and discussed with the customer. The service is carried out by Multitel’s experts and does not require the customer to be on site. Customer interactions can be organized remotely. The execution time depends on the complexity of the application, the available data and the agreed development activities, and is defined during the quotation phase. ###Use cases/examples **Example 1 – AI-based patient monitoring for neurodegenerative diseases** A healthcare technology developer needs an AI solution to extract objective indicators of motor function from video data. Multitel develops computer-vision and machine-learning components for motion capture and longitudinal monitoring, with the objective of deriving digital biomarkers relevant to neurological conditions such as Parkinson’s disease. **Outcome**: a customized AI component capable of supporting objective motion analysis and subsequent validation within the healthcare application. **Example 2 – Improvement of an AI model for medical image analysis** An SME already has an AI-driven solution for the automatic analysis of medical images but needs to improve its performance and development methodology. Multitel reviews the existing model and development pipeline, identifies improvement opportunities, and refines the model and associated evaluation approach. Depending on the need, the work can address performance, robustness, uncertainty estimation or traceability. **Outcome**: an improved AI solution together with technical evidence supporting further development and validation.

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