Clinical decision support systems are a combination of software techniques to help the clinicians in their medical decision making process via functionalities ranging from basic signal analysis to therapeutic planning and computerized guidelines. The algorithms providing all these functionalities must be very carefully validated on real patient data and must be confronted to everyday clinical practice. One of the main problems when developing these techniques is the difficulty to obtain high-quality complete patient records, comprising data coming both from the biomedical equipment (high-frequency signals), and from numerous other sources (therapeutics, imagery, clinical actions, etc.). In this paper, we present an infrastructure for developing and testing such software algorithms. It is based on a bedside workstation where testing different algorithms simultaneously on real-time data is possible in the ward. It is completed by a collaborative portal enabling different teams to test their software algorithms on the same patient records, making comparisons and cross-validations more easily.
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http://dx.doi.org/10.1016/j.cmpb.2008.07.012 | DOI Listing |
Rev Recent Clin Trials
January 2025
Dipartimento Patologia e Cura del Bambino, Regina Margherita AOU Città della Salute e della Scienza di Torino, Presidio Infantile Regina Margherita, Turin, Italy.
Background: Over the past decade, there has been a significant shift from paper-based to digital medical record management, driven largely by advances in digital technology. This transition has led to widespread adoption of Electronic Medical Records (EMRs), with the expectation that paper documentation will soon be fully replaced. In response, the European Medicines Agency's "Guideline on Computerised Systems in Clinical Trials" outlines essential criteria for validated EMR systems to ensure data integrity and security, and sets standards for electronic source documents in clinical trials.
View Article and Find Full Text PDFCochrane Database Syst Rev
January 2025
Cornell Joan Klein Jacobs Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, USA.
Background: Precision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.
View Article and Find Full Text PDFAm J Sports Med
January 2025
Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois, USA.
Background: Timely recognition and addressing of concomitant cartilage damage at the time of meniscal allograft transplantation (MAT) is critical to warrant future success. However, there remains a scarcity of data comparing outcomes between MAT with and without cartilage procedures.
Purpose: To compare patient-reported outcomes and rates of complications, failures, reoperations, and graft survivorship after MAT with concomitant cartilage procedures (MAT/Cart) and MAT without (MAT/NoCart).
JMIR Med Inform
January 2025
Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, United States.
Background: Studies suggest that less than 4% of patients with pulmonary embolisms (PEs) are managed in the outpatient setting. Strong evidence and multiple guidelines support the use of the Pulmonary Embolism Severity Index (PESI) for the identification of acute PE patients appropriate for outpatient management. However, calculating the PESI score can be inconvenient in a busy emergency department (ED).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Nutritional status is associated with prognosis in a variety of cancers. Studies analyzing the association between the measurements of skeletal muscle and adipose tissue obtained from Computerized Tomography (CT) images at the time of diagnosis of advanced non-small cell lung cancer (NSCLC) and overall survival (OS) are relatively few. Data from 425 patients diagnosed with advanced NSCLC between January 2016 and December 2017 were retrospectively analyzed, with an average follow-up of 15.
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