Event prediction in the big data era: A systematic survey

L Zhao - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Large-scale analysis of counseling conversations: An application of natural language processing to mental health

T Althoff, K Clark, J Leskovec - Transactions of the Association for …, 2016 - direct.mit.edu
Mental illness is one of the most pressing public health issues of our time. While counseling
and psychotherapy can be effective treatments, our knowledge about how to conduct …

Unsupervised learning of disease progression models

X Wang, D Sontag, F Wang - Proceedings of the 20th ACM SIGKDD …, 2014 - dl.acm.org
Chronic diseases, such as Alzheimer's Disease, Diabetes, and Chronic Obstructive
Pulmonary Disease, usually progress slowly over a long period of time, causing increasing …

Expecting to be hip: Hawkes intensity processes for social media popularity

MA Rizoiu, L **e, S Sanner, M Cebrian, H Yu… - Proceedings of the 26th …, 2017 - dl.acm.org
Modeling and predicting the popularity of online content is a significant problem for the
practice of information dissemination, advertising, and consumption. Recent work analyzing …

Predictive modeling of the progression of Alzheimer's disease with recurrent neural networks

T Wang, RG Qiu, M Yu - Scientific reports, 2018 - nature.com
The number of service visits of Alzheimer's disease (AD) patients is different from each other
and their visit time intervals are non-uniform. Although the literature has revealed many …

[HTML][HTML] Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns

S Ghosh, J Li, L Cao, K Ramamohanarao - Journal of biomedical …, 2017 - Elsevier
Background and objective Critical care patient events like sepsis or septic shock in intensive
care units (ICUs) are dangerous complications which can cause multiple organ failures and …

Eventthread: Visual summarization and stage analysis of event sequence data

S Guo, K Xu, R Zhao, D Gotz, H Zha… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Event sequence data such as electronic health records, a person's academic records, or car
service records, are ordered series of events which have occurred over a period of time …

Visual progression analysis of event sequence data

S Guo, Z **, D Gotz, F Du, H Zha… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Event sequence data is common to a broad range of application domains, from security to
health care to scholarly communication. This form of data captures information about the …

Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction

B Ljubic, S Roychoudhury, XH Cao, M Pavlovski… - Computer methods and …, 2020 - Elsevier
Background and objective Alzheimer's disease (AD) is the most common type of dementia
that can seriously affect a person's ability to perform daily activities. Estimates indicate that …

[책][B] Personalized machine learning

J McAuley - 2022 - books.google.com
Every day we interact with machine learning systems offering individualized predictions for
our entertainment, social connections, purchases, or health. These involve several …