Graphical Models for Continuous Time Inference and Decision Making

[1]  Frank Jensen,et al.  From Influence Diagrams to junction Trees , 1994, UAI.

[2]  Ahmed Y. Tawfik,et al.  Temporal Reasoning and Bayesian Networks , 2000, Comput. Intell..

[3]  Uffe Kjærulff,et al.  dHugin: a computational system for dynamic time-sliced Bayesian networks , 1995 .

[4]  Elpida T. Keravnou,et al.  A temporal reasoning framework used in the diagnosis of skeletal dysplasias , 1990, Artif. Intell. Medicine.

[5]  Sheldon M. Ross Introduction to Probability Models. , 1995 .

[6]  D. Heckerman,et al.  Integrated expert systems and videodisc in surgical pathology: an overview. , 1990, Human pathology.

[7]  Angelo Montanari,et al.  Temporal representation and reasoning in artificial intelligence: Issues and approaches , 2000, Annals of Mathematics and Artificial Intelligence.

[8]  J. Scott Provan,et al.  The Complexity of Counting Cuts and of Computing the Probability that a Graph is Connected , 1983, SIAM J. Comput..

[9]  Steffen L. Lauritzen,et al.  Representing and Solving Decision Problems with Limited Information , 2001, Manag. Sci..

[10]  Daphne Koller,et al.  Learning Continuous Time Bayesian Networks , 2002, UAI.

[11]  M A Musen,et al.  A Temporal Query System for Protocol-Directed Decision Support , 1994, Methods of Information in Medicine.

[12]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[13]  Hans-Peter Blossfeld,et al.  Unobserved heterogeneity in event history models , 1992 .

[14]  Christian R. Shelton,et al.  Solving Structured Continuous-Time Markov Decision Processes , 2008, ISAIM.

[15]  Ørnulf Borgan,et al.  Counting process models for life history data: a review , 1984 .

[16]  Thomas D. Nielsen Decomposition of Influence Diagrams , 2001, ECSQARU.

[17]  Bonnie Kaplan,et al.  Clinical decision support systems for the practice of evidence-based medicine. , 2001, Journal of the American Medical Informatics Association : JAMIA.

[18]  Yang Xiang,et al.  Multiply sectioned Bayesian networks for neuromuscular diagnosis , 1993, Artif. Intell. Medicine.

[19]  Hans-Peter Blossfeld,et al.  Event History Analysis: Statistical theory and Application in the Social Sciences , 2016 .

[20]  Finn Verner Jensen,et al.  Information enhancement - A tool for approximate representation of optimal strategies from influence diagrams , 2012, Int. J. Approx. Reason..

[21]  Nir Friedman,et al.  Gibbs Sampling in Factorized Continuous-Time Markov Processes , 2008, UAI.

[22]  Finn Verner Jensen,et al.  MUNIN: an expert EMG assistant , 1988 .

[23]  Jing Xu,et al.  Continuous Time Bayesian Networks for Host Level Network Intrusion Detection , 2008, ECML/PKDD.

[24]  James F. Allen Towards a General Theory of Action and Time , 1984, Artif. Intell..

[25]  Ronald A. Howard,et al.  Influence Diagrams , 2005, Decis. Anal..

[26]  David P. Miller,et al.  Temporal reasoning , 1986, WSC '86.

[27]  Daphne Koller,et al.  Continuous Time Bayesian Networks , 2012, UAI.

[28]  François Charpillet,et al.  A dynamic Bayesian network for handling uncertainty in a decision support system adapted to the monitoring of patients treated by hemodialysis , 2005, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05).

[29]  Ahmed Y. Tawfik,et al.  Temporal Bayesian Networks , 1994, TIME.

[30]  Henry A. Kautz,et al.  Extending Continuous Time Bayesian Networks , 2005, AAAI.

[31]  Daphne Koller,et al.  Expectation Maximization and Complex Duration Distributions for Continuous Time Bayesian Networks , 2005, UAI.

[32]  Niels Keiding,et al.  Statistical Models Based on Counting Processes , 1993 .

[33]  Joanne Bechta Dugan,et al.  A continuous-time Bayesian network reliability modeling, and analysis framework , 2006, IEEE Transactions on Reliability.

[34]  Keiji Kanazawa,et al.  A model for reasoning about persistence and causation , 1989 .

[35]  Jing Xu,et al.  Importance Sampling for Continuous Time Bayesian Networks , 2010, J. Mach. Learn. Res..

[36]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[37]  Eric Horvitz,et al.  Continuous Time Bayesian Networks for Inferring Users’ Presence and Activities with Extensions for Modeling and Evaluation , 2003 .

[38]  Peter van Beek,et al.  Exact and approximate reasoning about temporal relations 1 , 1990, Comput. Intell..

[39]  Isabelle Bichindaritz,et al.  Temporal knowledge representation and organization for case-based reasoning , 1996, Proceedings Third International Workshop on Temporal Representation and Reasoning (TIME '96).

[40]  Stuart J. Russell,et al.  Dynamic bayesian networks: representation, inference and learning , 2002 .

[41]  Finn Verner,et al.  Information enhancement for approximate representation of optimal strategies from in uence diagrams , 2010 .

[42]  D. Heckerman,et al.  Toward Normative Expert Systems: Part I The Pathfinder Project , 1992, Methods of Information in Medicine.

[43]  Prakash P. Shenoy,et al.  Local Computation in Hypertrees , 1991 .

[44]  M G Kahn,et al.  Creating temporal abstractions in three clinical information systems. , 1995, Proceedings. Symposium on Computer Applications in Medical Care.

[45]  Gregory F. Cooper,et al.  The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks , 1990, Artif. Intell..

[46]  Clyde W. Holsapple,et al.  Handbook on Decision Support Systems 2: Variations , 2008 .

[47]  Fabio Stella,et al.  A continuous time Bayesian network model for cardiogenic heart failure , 2012 .

[48]  Juan Carlos Augusto,et al.  The Logical Approach to Temporal Reasoning , 2001, Artificial Intelligence Review.

[49]  李幼升,et al.  Ph , 1989 .

[50]  Peter J. F. Lucas,et al.  Dynamic Bayesian networks as prognostic models for clinical patient management , 2008, J. Biomed. Informatics.

[51]  Anders Fuglsang-Frederiksen,et al.  PC-KANDID: An expert system for electromyography , 1989, Artif. Intell. Medicine.

[52]  Jonathan Stillman,et al.  Tachyon: a constraint-based temporal reasoning model and its implementation , 1993, SGAR.

[53]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[54]  Tom Minka,et al.  Expectation Propagation for approximate Bayesian inference , 2001, UAI.

[55]  H. Lehmann,et al.  Clinical Decision Support Systems (cdsss) Have Been Hailed for Their Potential to Reduce Medical Errors Clinical Decision Support Systems for the Practice of Evidence-based Medicine , 2022 .

[56]  F Pinciroli,et al.  Managing Different Time Granularities of Clinical Information by an Interval-based Temporal Data Model , 1995, Methods of Information in Medicine.

[57]  H. Mcdonald,et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. , 2005, JAMA.

[58]  D. Mozaffarian,et al.  The Seattle Heart Failure Model: Prediction of Survival in Heart Failure , 2006, Circulation.

[59]  W. R. Shao,et al.  Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis , 2008 .

[60]  Raymond Reiter,et al.  Reasoning about time in the situation calculus , 1995, Annals of Mathematics and Artificial Intelligence.

[61]  Salim Yusuf,et al.  A multivariate model for predicting mortality in patients with heart failure and systolic dysfunction. , 2004, The American journal of medicine.

[62]  Barrie Lipscombe,et al.  Expert systems and computer-controlled decision making in medicine , 1989, AI & SOCIETY.

[63]  David J. Spiegelhalter,et al.  Probabilistic Networks and Expert Systems , 1999, Information Science and Statistics.

[64]  Ronald A. Howard,et al.  Readings on the Principles and Applications of Decision Analysis , 1989 .

[65]  Yuval Shahar,et al.  Temporal Information Systems in Medicine , 2010 .

[66]  P. Allison Event History Analysis , 1984 .

[67]  G. P. Bhattacharjee,et al.  Temporal representation and reasoning in artificial intelligence: A review , 2001 .

[68]  Nir Friedman,et al.  Probabilistic Graphical Models - Principles and Techniques , 2009 .

[69]  Lester Lipsky,et al.  Queueing Theory: A Linear Algebraic Approach , 1992 .

[70]  Brendan Murphy,et al.  Structure from failure , 2007 .

[71]  Yves Besnard,et al.  Neurop: An Expert System In Electromyography Based On A Multilevel Knowledge Representation , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[72]  Juan Carlos Augusto,et al.  Temporal reasoning for decision support in medicine , 2005, Artif. Intell. Medicine.

[73]  Federico M. Stefanini,et al.  Using Weak Prior Information on Structures to Learn Bayesian Networks , 2007, KES.

[74]  Yu Fan,et al.  Learning Continuous-Time Social Network Dynamics , 2009, UAI.

[75]  Lawrence M. Fagan,et al.  Extensions to the Time-Oriented Database Model to Support Temporal Reasoning in Medical Expert Systems , 1991, Methods of Information in Medicine.

[76]  Alvin W Drake,et al.  Observation of a Markov process through a noisy channel , 1962 .

[77]  Sushil Jajodia,et al.  Time Granularities in Databases, Data Mining, and Temporal Reasoning , 2000, Springer Berlin Heidelberg.

[78]  Cleve B. Moler,et al.  Nineteen Dubious Ways to Compute the Exponential of a Matrix, Twenty-Five Years Later , 1978, SIAM Rev..

[79]  Thomas D. Nielsen,et al.  Advances in Decision Graphs , 2004 .

[80]  Eric Horvitz,et al.  Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base Part II , 2016 .

[81]  Hans-Peter Blossfeld,et al.  Techniques of event history modeling : new approaches to causal analysis , 2001 .

[82]  M.T. Arredondo,et al.  Bayesian networks and influence diagrams as valid decision support tools in systolic heart failure management , 2004, Computers in Cardiology, 2004.

[83]  Nir Friedman,et al.  Continuous Time Markov Networks , 2006, UAI.

[84]  Gultekin Özsoyoglu,et al.  Temporal and Real-Time Databases: A Survey , 1995, IEEE Trans. Knowl. Data Eng..

[85]  Marek J Druzdzel,et al.  Relevance in Probabilistic Models: "Backyards" in a "Small World" , 1994 .

[86]  Kazuo Yamaguchi,et al.  Event History Analysis. , 1992 .

[87]  Avi Pfeffer,et al.  Continuous Time Particle Filtering , 2005, IJCAI.

[88]  M P Beddoes,et al.  Quality control in nerve conduction studies with coupled knowledge‐based system approach , 1992, Muscle & nerve.

[89]  Annick Vila,et al.  Experimental EMG expert system as an aid in diagnosis , 1985 .

[90]  Kevin B. Korb,et al.  Epidemiological data mining of cardiovascular Bayesian networks , 2006 .

[91]  Henry A. Kautz,et al.  Constraint propagation algorithms for temporal reasoning: a revised report , 1989 .

[92]  Luis Enrique Sucar,et al.  A Temporal Bayesian Network for Diagnosis and Prediction , 1999, UAI.

[93]  Isaac S. Kohane TEMPORAL REASONING IN MEDICAL EXPERT SYSTEMS , 1987 .

[94]  D. McDermott A Temporal Logic for Reasoning About Processes and Plans , 1982, Cogn. Sci..

[95]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[96]  Yu Fan,et al.  Sampling for Approximate Inference in Continuous Time Bayesian Networks , 2008, ISAIM.