In 1854, London experienced an epidemic of cholera that took more than 500 lives. In September of that year, Dr. John Snow plotted the locations of cases and of water pumps throughout the city. Using simple graphical analysis, Dr. Snow quickly identified that the source of the epidemic was the Broad Street water pump. He had the handle removed, and the cholera breakout ended. While computational analysis might have resulted in the same solution set eventually, the proper visualization of the data provided a quick solution whichprobably saved lives (Tufte, 2002). Health professionals must therefore understand that graphical analysis of data is critical to the understanding of multidimensional relationships. The following discussion illustrates the importance of data visualization as applied to the field of healthcare. We begin with an examination F.J. Anscombe's and Edward Tufte's important works regarding graphical analysis.
Download full-text PDF |
Source |
---|
Background Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR. Methods Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
View Article and Find Full Text PDFUnlabelled: The organizational principles that distinguish the human brain from other species have been a long-standing enigma in neuroscience. Focusing on the uniquely evolved human cortical layers 2 and 3, we computationally reconstruct the cortical architecture for mice and humans. We show that human pyramidal cells form highly complex networks, demonstrated by the increased number and simplex dimension compared to mice.
View Article and Find Full Text PDFExpert Rev Endocrinol Metab
January 2025
Faculty of Medicine, University of Cyberjaya, Cyberjaya, Malaysia.
Background: The rapid rise of non-communicable diseases, particularly type 2 diabetes mellitus (T2DM), poses a significant global public health challenge, with South Asia experiencing an increasingly severe burden. This study aimed to analyse historical trends of T2DM across South Asia from 1990 to 2021 and forecast incidence through 2031.
Research Design And Methods: We carried out analysis based on the data from the 2021 Global burden of disease study.
Sci Rep
January 2025
Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran.
Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.
View Article and Find Full Text PDFNeuropsychologia
January 2025
McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia SC 29016, USA. Electronic address:
Visualization software is a critical component at every stage of neuroimaging research. It enables researchers to inspect raw or processed datasets for artifacts, to identify anomalies, to verify the accuracy of automated processing, and to interpret the location of statistical results within the complex structure of the human brain. Since 2006, MRIcron has provided a free, open-source, cross-platform tool designed to meet these needs.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!