Tind Technologies (Norway)
Hes-so: ArODES Open Archive (University of Applied Sciences and Arts Western Switzerland / Haute école spécialisée de Suisse occidentale / FH Westschweiz)Not a member yet
15764 research outputs found
Sort by
Structured radiology report text analysis using natural language processing for automatic billing
No full textPurpose: The aim of this study was to develop an algorithm for automated quality control of structured radiology reports and to automatically obtain the correct invoicing codes for the performed exam. Ultrasound (US) exams of the abdomen were selected as use case, including Doppler exams. Method: To build a correct algorithm for automatic billing, the billing tree for the Ultrasound exams was studied. In Switzerland, TARMED, is the tariff structure used for billing outpatient medical services. The 4600 services listed in TARMED are divided into chapters that group together all services with a well-defined common characteristic. For example, Chapter 39 covers all medical imaging services. These chapters are further subdivided into subchapters for greater precision. Using this information a modular Natural Language Processing algorithm based on the Natural Language Toolkit (NLTK) library was developed. A second NLP algorithm based on SPACY was also developed, with the objective of a double validation of the first developed NLP algorithm. To train and test the algorithm a dataset of 170 exams corresponding to US abdominal examinations along with their radiology report were extracted from our RIS. The results of the algorithm were validated by an experienced technologists which identified possible discrepancy between the algorithm results and the correct billing. This check was carried out on a batch of data containing 95 samples. A confusion matrix was used to analyze the results. Results: In all 95 data samples, the NLTK algorithm was able to detect the billing codes correctly 100% of the time. In all our 95 data samples, the Spacy algorithm was able to detect the billing codes correctly in 86.3% of cases. This algorithm tends to overestimate the type of abdominal examination present in the report. Indeed, the 13 cases in which the algorithm made an error were cases where it detected a full abdominal ultrasound when the examination was a simple lower or upper abdomen. Conclusion: The NLTK model provides reliable and efficient estimation of billing codes for abdominal ultrasound, facilitating the task of the technologies who saves time and avoids possible human errors
From chains to chains ::blockchain innovations in combating modern slavery and enhancing reporting mechanisms
No full textAutomatic cranial defect reconstruction with self-supervised deep deformable masked autoencoders
No full textThousands of people suffer from cranial injuries every year. They require personalized implants that need to be designed and manufactured before the reconstruction surgery. The manual design is expensive and time-consuming leading to searching for algorithms whose goal is to automatize the process. The problem can be formulated as volumetric shape completion and solved by deep neural networks dedicated to supervised image segmentation. However, such an approach requires annotating the ground-truth defects which is costly and time-consuming. Usually, the process is replaced with synthetic defect generation. However, even the synthetic ground-truth generation is time-consuming and limits the data heterogeneity, thus the deep models’ generalizability. In our work, we propose an alternative and simple approach to use a self-supervised masked autoencoder to solve the problem. This approach by design increases the heterogeneity of the training set and can be seen as a form of data augmentation. We compare the proposed method with several state-of-the-art deep neural networks and show both the quantitative and qualitative improvement on the SkullBreak and SkullFix datasets. The proposed method can be used to efficiently reconstruct the cranial defects in real time
Overview of ImageCLEFmedical 2024 – caption prediction and concept detection
No full textThe ImageCLEFmedical 2024 Caption task on caption prediction and concept detection follows similar challenges held from 2017–2023. The goal is to extract Unified Medical Language System (UMLS) concept annotations and/or define captions from image data. Predictions are compared to original image captions. Images for both tasks are part of the Radiology Objects in COntext version 2 (ROCOv2) dataset. For concept detection, multi-label predictions are compared against UMLS terms extracted from the original captions with additional manually curated concepts via the F1-score. For caption prediction, the semantic similarity of the predictions to the original captions is evaluated using the BERTScore. The task attracted strong participation with 50 registered teams,14 teams submitted 82 graded runs for the two subtasks. Participants mainly used multi-label classification systems for the concept detection subtask, the winning team DBS-HHU utilized an ensemble of four different Convolutional Neural Networks (CNNs). For the caption prediction subtask, most teams used encoder-decoder frameworks with various backbones, including transformer-based decoders and Long Short-Term Memories (LSTMs), with the winning team PCLmed using medical vision-language foundation models (Med-VLFMs) by combining general and specialist vision models
Evaluation of traffic controller performance via systematic exploration
No full textTraffic controllers must operate reliably across diverse traffic states. Due to the stochastic non-linear characteristics of traffic flow, commonly used feedback-based controllers require parameter tuning for each specific traffic regime, which is done offline using simulations. Generating representative traffic scenarios for large-scale simulations is often computationally expensive. To reduce the computational burden, this paper proposes a systematic exploration of the Structured Simulation Framework (SSF). This approach aims to approximate controller performance with a minimal number of simulations, by adjusting the parameter space continuously to regions where controller performances are weakly approximated. This process continues until controller performance is well approximated across the entire input domain. Results show SSF convergence of performance estimate of the controller while reducing the number of required simulations. This helps identify traffic scenarios where the controller performs poorly, and, thus, can be used as a framework towards guided controller tuning
Tabita Rezaire ::a megalithic space program
No full textTabita Rezaire is an interdisciplinary artist and activist exploring the intersections between technology, spirituality, decolonization and healing. She uses video, performance art and the creation of immersive spaces to challenge hegemonic narratives and advocate a holistic understanding of the world in which realities are interconnected. Her work focuses on the decolonization of knowledge and on researching the ways in which patriarchal and power structures shape our perception and use of technology. Rezaire’s work salvages ancestral knowledges and practices that were marginalized or silenced, and merges indigenous, African and non-Western knowledges with digital technologies to explore how spiritual and healing practices can be used as tools for resistance, emancipation and reconstruction of identities and communities
The manufacture of type for typewriters in Switzerland
No full textBetween the 1940s and the 1990s, three companies manufactured type components for typewriters in Switzerland: Caractères SA, Setag, and Novatype. For more than fifty years, they supplied the biggest manufacturers of office machines in Europe and around the world, such as IBM, Remington, Olivetti, Paillard-Hermès, and Triumph-Adler. Having held a leading position worldwide, the three manufacturers played a key role in the design, development, and production of type components and typefaces for typewriters, as well as for all kinds of impact printers. By looking in detail at their production methods, this article observes what influence the manufacturing processes and the mechanical characteristics of the typewriter had on the design of the typefaces. Additionally, it takes an interest in the surprising role played by the criminal police. Specialized in the dating and identification of typewriter typefaces for judicial and
criminal purposes, forensic experts developed over the years specific methods and compiled rich documentation on typewriter typefaces. Being in direct contact with the type manufacturers to gain first-hand information, they even interfered in the design of some letter shapes. Based on oral history and archival research, this project sheds light on this little-known part of the industrial and typographic history
The single-layer equivalent soil mass method for the evaluation of soil organic carbon stocks::sources of errors, simplification, and associated detectable change
No full textIt has been well established that for consistent soil organic carbon stock (SOCS) monitoring over time, the SOCS must be determined in an equivalent soil mass (ESM) layer rather than a depth layer. This work focused on the single-layer ESM method, its cost, accuracy and simplification. With the objective of simplifying ESM method and reducing costs, we sampled 393 fields in western Switzerland and experimentally questioned the sampling methods, the sources of variance and the minimum detectable change (MDC) of SOCS, and possible simplification. The layer mass was accurately determined using gouge-augers, thus overcoming a major drawback in performing ESM SOCS evaluation. The relationships between number of aliquots and estimated SOCS variance was determined. Sampling at fixed depth and layer bulk density resulted in unacceptable errors and MDCs exceeding several decades when converted to years before a change was detectable. We introduced a new procedure to fully consider the coarse fraction volume in the layer, which remains a major source of error on the SOCS when the coarse fraction volume exceeds 10 % of the layer volume, while not impacting the detectability of the change. The single-layer ESM method provided an MDC corresponding to less than 10 years before SOCS change detectability under the average regional conditions, and mass correction results in negligible increase in MDC compared to that of the 0–30 cm layer. Simplifying this method by using the average soil organic carbon content of the layer mass correction only slightly increased the MDC, thus providing an opportunity to decrease the cost of SOCS monitoring significantly
Design and development of pilot photobioreactor for simultaneous microalgae cultivation and aquaculture wastewater treatment
No full textThis study presents an innovative and modular phototrophic biofilm photobioreactor (PBR) designed for the simultaneous cultivation of algae and the treatment of aquaculture wastewater (AWW). The vertical flat-plate BPR allows for stable microalgae growth while efficiently removing nutrients from wastewater under controlled conditions, including light, CO2, supplementation, water recirculation and continuous monitoring of parameters such as pH, nitrate (NO3-N) and phosphate (PO43-P). The PBR was operated at an aquaculture facility using AWW, with nutrient removal and microalgal growth being monitored. The microalgae consortium composed of Chlorella sp., Scenedesmus sp. and Phormidium sp. were evaluated for their growth potential and wastewater remediation capabilities. Results showed high nutrient removal efficiencies with 92 % reduction of PO43-P (removal rate: 0.07 mg/L d) and a 62 % reduction of NO3--N (removal rate: 1.1 mg/L d), bringing nutrient concentrations below the limits set by the Waters Protection Ordinance. Maximum biomass production reached a growth rate on land surface of 25 g/m2/d, with a favorable biochemical composition of 51 % proteins, 25 % carbohydrates and up to 8 % lipids, indicating the potential for use animal feed. This study demonstrates the feasibility of using AWW as a growth medium for microalgae while simultaneously achieving wastewater remediation, offering a sustainable solution for nutrient recycling in aquaculture operations
