Publications

Refine Results

(Filters Applied) Clear All

A multi-task LSTM framework for improved early sepsis prediction

Published in:
Proc. Artificial Intelligence in Medicine, AIME, 2020, pp. 49-58.

Summary

Early detection for sepsis, a high-mortality clinical condition, is important for improving patient outcomes. The performance of conventional deep learning methods degrades quickly as predictions are made several hours prior to the clinical definition. We adopt recurrent neural networks (RNNs) to improve early prediction of the onset of sepsis using times series of physiological measurements. Furthermore, physiological data is often missing and imputation is necessary. Absence of data might arise due to decisions made by clinical professionals which carries information. Using the missing data patterns into the learning process can further guide how much trust to place on imputed values. A new multi-task LSTM model is proposed that takes informative missingness into account during training that effectively attributes trust to temporal measurements. Experimental results demonstrate our method outperforms conventional CNN and LSTM models on the PhysioNet-2019 CiC early sepsis prediction challenge in terms of area under receiver-operating curve and precision-recall curve, and further improves upon calibration of prediction scores.
READ LESS

Summary

Early detection for sepsis, a high-mortality clinical condition, is important for improving patient outcomes. The performance of conventional deep learning methods degrades quickly as predictions are made several hours prior to the clinical definition. We adopt recurrent neural networks (RNNs) to improve early prediction of the onset of sepsis using...

READ MORE

The Human Trafficking Technology Roadmap: a targeted development strategy for the Department of Homeland Security

Summary

Human trafficking is a form of modern-day slavery that involves the use of force, fraud, or coercion for the purposes of involuntary labor and sexual exploitation. It affects tens of million of victims worldwide and generates tens of billions of dollars in illicit profits annually. While agencies across the U.S. Government employ a diverse range of resources to combat human trafficking in the U.S. and abroad, trafficking operations remain challenging to measure, investigate, and interdict. Within the Department of Homeland Security, the Science and Technology Directorate is addressing these challenges by incorporating computational social science research into their counter-human trafficking approach. As part of this approach, the Directorate tasked an interdisciplinary team of national security researchers at the Massachusetts Institute of Technology's Lincoln Laboratory, a federally funded research and development center, to undertake a detailed examination of the human trafficking response across the Homeland Security Enterprise. The first phase of this effort was a government-wide systems analysis of major counter-trafficking thrust areas, including law enforcement and prosecution; public health and emergency medicine; victim services; and policy and legislation. The second phase built on this systems analysis to develop a human trafficking technology roadmap and implementation strategy for the Science and Technology Directorate, which is presented in this document.
READ LESS

Summary

Human trafficking is a form of modern-day slavery that involves the use of force, fraud, or coercion for the purposes of involuntary labor and sexual exploitation. It affects tens of million of victims worldwide and generates tens of billions of dollars in illicit profits annually. While agencies across the U.S...

READ MORE

Showing Results

1-2 of 2