Related Experiment Video
Updated: Feb 8, 2026

Learning Modern Laryngeal Surgery in a Dissection Laboratory
Published on: March 18, 2020
History of disruptions in laboratory medicine: what have we learned from predictions?
1Professor Emeritus, Department of Pathology and Laboratory Medicine, University of Pennsylvania Medical Center, Philadelphia, PA 19104, USA.
Abstract:
Predictions about the future of laboratory medicine have had a mixed success, and in some instances they have been overambitious and incorrectly assessed the future impact of emerging technologies. Current predictions suggest a more highly automated and connected future for diagnostic testing. The central laboratory of the future may be dominated by more robotics and more connectivity in order to take advantage of the benefits of the Internet of Things and artificial intelligence (AI)-based systems (e.g. decision support software and imaging analytics). For point-of-care testing, mobile health (mHealth) may be in the ascendancy driven by healthcare initiatives from technology companies such as Amazon, Apple, Facebook, Google, IBM, Microsoft and Uber.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
09:23JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning
Published on: March 21, 2025
Related Concept Videos
What is Evolutionary History?
Life Histories
History of Microbiology
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Nursing Assessment of the Genitourinary System I: Health History