Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Advances in intense femtosecond laser filamentation in air

This is a review of some recent development in femtosecond filamentation science with emphasis on our collective work. Previously reviewed work in the field will not be discussed. We thus start with a very brief description of the fundamental physics of single filamentation of powerful femtosecond laser pulses in air. Intensity clamping is emphasized. One consequence is that the peak intensity inside one or more filaments would not increase significantly even if one focuses the pulse at very high peak power even up to the peta-watt level. Another is that the clamped intensity is independent of pressure. One interesting outcome of the high intensity inside a filament is filament fusion which comes from the nonlinear change of index of refraction inside the filament leading to cross beam focusing. Because of the high intensity inside the filament, one can envisage nonlinear phenomena taking place inside a filament such as a new type of Raman red shift and the generation of very broad band supercontinuum into the infrared through four-wave-mixing. This is what we call by filamentation nonlinear optics. It includes also terahertz generation from inside the filament. The latter is discussed separately because of its special importance to those working in the field of safety and security in recent years. When the filamenting pulse is linearly polarized, the isotropic nature of air becomes birefringent both electronically (instantaneous) and through molecular wave packet rotation and revival (delayed). Such birefringence is discussed in detailed. Because, in principle, a filament can be projected to a long distance in air, applications to pollution measurement as well as other atmospheric science could be earned out. We call this filamentation atmospheric science. Thus, the following subjects are discussed briefly, namely, lightning control, rain making, remote measurement of electric field, microwave guidance and remote sensing of pollutants. A discussion on the higher order Kerr effect on the physics of filamentation is also given. This is a new hot subject of current debate. This review ends on giving our view of the prospect of progress of this field of filamentation in the future. We believe it hinges upon the development of the laser technology based upon the physical understanding of filamentation and on the reduction in price of the laser system

Filamentation ''remote'' sensing of chemical and biological agents/pollutants using only one femtosecond laser source

International audienceAll matters in the path of filaments induced by an intense femtosecond laser pulse propagating in air could be fragmented and result in the emission of characteristic fluorescence spectra from the excited fragments. The fluorescence spectra exhibit specific signatures (fingerprints) that can be used for the identification of various substances including chemical and biological species. In this paper, we present an overview of the recent progress in our laboratory concerning the "remote" sensing of chemical and biological agents/pollutants in air using filamentation-induced nonlinear fluorescence techniques