Toward better public health reporting using existing off the shelf approaches: The value of medical dictionaries in automated cancer detection using plaintext medical data

Objectives Existing approaches to derive decision models from plaintext clinical data frequently depend on medical dictionaries as the sources of potential features. Prior research suggests that decision models developed using non-dictionary based feature sourcing approaches and “off the shelf” tools could predict cancer with performance metrics between 80% and 90%. We sought to compare non-dictionary based models to models built using features derived from medical dictionaries. Materials and methods We evaluated the detection of cancer cases from free text pathology reports using decision models built with combinations of dictionary or non-dictionary based feature sourcing approaches, 4 feature subset sizes, and 5 classification algorithms. Each decision model was evaluated using the following performance metrics: sensitivity, specificity, accuracy, positive predictive value, and area under the receiver operating characteristics (ROC) curve. Results Decision models parameterized using dictionary and non-dictionary feature sourcing approaches produced performance metrics between 70 and 90%. The source of features and feature subset size had no impact on the performance of a decision model. Conclusion Our study suggests there is little value in leveraging medical dictionaries for extracting features for decision model building. Decision models built using features extracted from the plaintext reports themselves achieve comparable results to those built using medical dictionaries. Overall, this suggests that existing “off the shelf” approaches can be leveraged to perform accurate cancer detection using less complex Named Entity Recognition (NER) based feature extraction, automated feature selection and modeling approaches

Development of a portable bioimpedance monitor system for Chronic Kidney Disease Patients and high performance athletes

El presente artículo da cuenta de la investigación para la innovación, diseño y desarrollo industrial de un dispositivo médico portable que obtiene datos relevantes de la bioimpedancia humana con precisión clínica, desarrollado en el Grupo de Ingeniería Biomédica de la Universidad de Sevilla en conjunto con el Tecnológico de Costa Rica para su diseño industrial. Los sistemas de bioimpedancia son una saliente novedosa en el campo de la e-salud, sin embargo, el incremento de la expectativa de vida y la inclusión de tecnología de monitoreo en aplicaciones deportivas han aumentado la necesidad de dispositivos médicos más portables, precisos y comerciables a nivel masivo, con el objetivo de empoderar al usuario sobre su situación médica. El método utilizado fue una investigación cualitativa centrada en el usuario mediante una metodología guía desarrollada por el autor, el modelo Divergente-Convergente Proyectual (DGC) centrado en el usuario. Los hallazgos más importantes fueron el diseño novedoso de un bioimpedancímetro portable para pacientes con afecciones renales crónicas y deportistas de alto rendimiento, así como el uso de una metodología novedosa para el desarrollo de productos médicos portables.The following article presents the research and innovation in the industrial design and development of a portable bioimpedance monitor system with clinical precision developed by the Biomedical Engineering Group of the University of Seville and with the Costa Rica Institute of Technology regarding the industrial design. Bioimpedance systems possess industrial design challenges for its application in the e-health field, even though, the continuous increase in life expectancy and the need for more precise medical equipment for sport applications have risen the need for portable and precise medical equipment that can be mass scaled commercialized and empower the user ́s healthcare situation. A qualitative approach method was used with a methodology designed by the author (Divergent-Convergent Project (DGC) Method). The most important findings were the industrial design and development of the bioimpedance monitor system and the novel methodology for the development of novel portable medical products