Mining electronic health records (EHRs) A survey
The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
Machine learning for data-centric epidemic forecasting
The COVID-19 pandemic emphasized the importance of epidemic forecasting for decision
makers in multiple domains, ranging from public health to the economy. Forecasting …
makers in multiple domains, ranging from public health to the economy. Forecasting …
Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion
Abstract Nowadays, Artificial intelligence (AI), combined with the digitalization of healthcare,
can lead to substantial improvements in Patient Care, Disease Management, Hospital …
can lead to substantial improvements in Patient Care, Disease Management, Hospital …
Anomaly detection with score distribution discrimination
Recent studies give more attention to the anomaly detection (AD) methods that can leverage
a handful of labeled anomalies along with abundant unlabeled data. These existing …
a handful of labeled anomalies along with abundant unlabeled data. These existing …
Slimfast: Guaranteed results for data fusion and source reliability
We focus on data fusion, ie, the problem of unifying conflicting data from data sources into a
single representation by estimating the source accuracies. We propose SLiMFast, a …
single representation by estimating the source accuracies. We propose SLiMFast, a …
[HTML][HTML] Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases
L Zhang, W Guo, C Lv - Science in One Health, 2024 - Elsevier
Background Zoonotic diseases originating in animals pose a significant threat to global
public health. Recent outbreaks, such as coronavirus disease 2019 (COVID-19), have …
public health. Recent outbreaks, such as coronavirus disease 2019 (COVID-19), have …
EMBERS at 4 years: Experiences operating an open source indicators forecasting system
EMBERS is an anticipatory intelligence system forecasting population-level events in
multiple countries of Latin America. A deployed system from 2012, EMBERS has been …
multiple countries of Latin America. A deployed system from 2012, EMBERS has been …
Characterizing diseases from unstructured text: A vocabulary driven word2vec approach
Traditional disease surveillance can be augmented with a wide variety of real-time sources
such as, news and social media. However, these sources are in general unstructured and …
such as, news and social media. However, these sources are in general unstructured and …
Temporal topic modeling to assess associations between news trends and infectious disease outbreaks
In retrospective assessments, internet news reports have been shown to capture early
reports of unknown infectious disease transmission prior to official laboratory confirmation. In …
reports of unknown infectious disease transmission prior to official laboratory confirmation. In …
Using social sensors for detecting emergency events: a case of power outages in the electrical utility industry
K Bauman, A Tuzhilin, R Zaczynski - ACM Transactions on Management …, 2017 - dl.acm.org
This article presents a novel approach to detecting emergency events, such as power
outages, that utilizes social media users as “social sensors” for virtual detection of such …
outages, that utilizes social media users as “social sensors” for virtual detection of such …