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  1. 1. Challenges for Artificially Intelligent Medical Devices in the Nordics and Suggested Strategies to Respond

    University essay from Lunds universitet/Innovationsteknik

    Author : Alva Rampe; Linea Holström; [2024]
    Keywords : Artificial Intelligence; Medical Device; HealthTech; Innovation Barriers; Technology and Engineering;

    Abstract : With aging populations, unequal access to care, and shortages of staff, healthcare systems today are facing many challenges. Technology advancements, with artificial intelligence (AI) in particular, have been one of the main drivers of innovation in multiple industries. READ MORE

  3. 2. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

    University essay from Lunds universitet/Fysiska institutionen

    Author : Max Svensson; [2024]
    Keywords : Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

    Abstract : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. READ MORE

  4. 3. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Bushra Alsabbagh; [2023]
    Keywords : Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Abstract : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. READ MORE

  5. 4. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions

    University essay from KTH/Matematik (Avd.)

    Author : Giorgio Sacchi; [2023]
    Keywords : Explainable AI; Counterfactual Explanations CFEs ; Bayesian Optimization BO ; Black-Box Models; Model-Agnostic; Machine Learning ML ; Efficient Computation; High-Stake Decisions; Förklarbar AI; Kontrafaktuell Förklaring CFE ; Bayesiansk Optimering BO ; Svarta lådmodeller; Modellagnostisk; Maskininlärning; Beräkningsmässigt Effektiv; Beslut med höga insatser;

    Abstract : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. READ MORE

  6. 5. Improving customer support efficiency through decision support powered by machine learning

    University essay from Linköpings universitet/Programvara och system

    Author : Simon Boman; [2023]
    Keywords : Machine Learning; AI; NLP; Natural Language Processing; GPT-3; GPT-4; Recommendation System; Decision Support; Semantic Textual Similarity; Text Similarity; Customer Support Tickets; Case Study; Customer Support Efficiency; Healthcare; Medical Technology;

    Abstract : More and more aspects of today’s healthcare are becoming integrated with medical technology and dependent on medical IT systems, which consequently puts stricter re-quirements on the companies delivering these solutions. As a result, companies delivering medical technology solutions need to spend a lot of resources maintaining high-quality, responsive customer support. READ MORE