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This article describes a new approach for quantitative evaluation of respiration in the pediatric intensive care unit (PICU). Video sequences of thorax movements are recorded by two depth cameras to cover the 3-D surface of the torso and its lateral sides. The breathing activity implies a frame-by-frame surface deformation, which can be described by the volume variation of reconstructed surfaces between the consecutive video frames. A quantitative evaluation of the breathing pattern is then performed through a subtraction technique, thereby detecting the volume variation between the subsequent frames. A high-fidelity simulation was performed in a realistic environment designed for critically ill children. The simulation was then followed by a real-world evaluation, involving two newborn babies (one female and one male) who required ventilator support. The breathing signal patterns resulting from our approach were compared to those measured by mechanical ventilation in terms of their waveforms, evaluating the most significant dynamic parameters: tidal volume, respiratory rate, and minute ventilation. Our experimental study showed a significant agreement between the proposed 3-D imaging system and the gold standard method in estimating respiratory waveforms and parameters. This article presents the following innovations. First, we suggest a 3-D imaging system specifically designed for PICUs based on a contactless design. Second, we propose an efficient positioning mechanism for the cameras, offering a very high spatial coverage of the thoracoabdominal zone and considering the PICU constraints. Finally, we propose an objective vision-based method to quantitatively measure respiration for spontaneous breathing patients in PICUs. [ABSTRACT FROM AUTHOR]

The Digital Imaging and Communications in Medicine (DICOM) standard recently introduced rules for the encoding, transmission and storage of the structured diagnostic report. This medical document can be stored and communicated with the images. It has a structure and may contain text, with links to other data such as images, waveforms and spatial or temporal coordinates. The prompt availability of the radiology report is crucial for implementing a Patient Electronic Record. Using the extensible markup language (XML) to encode the radiology report broadens its accessibly. This paper presents a document type definition (DTD) that accurately models the DICOM structured report content, structure, and constraints. [ABSTRACT FROM AUTHOR]

Learn how the Cross-Enterprise Document Sharing (XDS) integration profile helped provide the interoperability necessary to deploy electronic health records, giving healthcare providers access to medical records regardless of location or institution. [ABSTRACT FROM AUTHOR]

The rapid progress in clinical data management systems and artificial intelligence approaches enable the era of personalized medicine. Intensive care units (ICUs) are ideal clinical research environments for such development because they collect many clinical data and are highly computerized. Goal: We designed a retrospective clinical study on a prospective ICU database using clinical natural language to help in the early diagnosis of heart failure in critically ill children. Methods: The methodology consisted of empirical experiments of a learning algorithm to learn the hidden interpretation and presentation of the French clinical note data. This study included 1386 patients' clinical notes with 5444 single lines of notes. There were 1941 positive cases (36% of total) and 3503 negative cases classified by two independent physicians using a standardized approach. Results: The multilayer perceptron neural network outperforms other discriminative and generative classifiers. Consequently, the proposed framework yields an overall classification performance with 89% accuracy, 88% recall, and 89% precision. Conclusions: This study successfully applied learning representation and machine learning algorithms to detect heart failure in a single French institution from clinical natural language. Further work is needed to use the same methodology in other languages and institutions.

The temperature distribution at the skin surface could be a useful tool to monitor changes in cardiac output. Goal: The aim of this study was to explore infrared thermography as a method to analyze temperature profiles of critically ill children. Methods: Patients admitted to the pediatric intensive care unit (PICU) were included in this study. An infrared sensor was used to take images in clinical conditions. The infrared core and limb temperatures (θ c & θ l ) were extracted, as well as temperatures along a line drawn between these two regions. Results: The median [interquartile range] θ c extracted from the images was 33.88°C [32.74-34.19] and the median θ l was 30.21°C [28.89-33.13]. There was a good correlation between the θ c and the clinical axillary temperature (rho = 0.39, p-value = 0.016). There was also a good correlation between the θ c and θ l (rho = 0.66, p-value = 1.2 e -05 ). Conclusion: Thermography was found to be effective to estimate the body temperature. Correlation with specific clinical conditions needs further study.