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Predictive Business Process Monitoring Considering Reliability Estimates [chapter]

Andreas Metzger, Felix Föcker
2017 Lecture Notes in Computer Science  
Predictive business process monitoring aims at predicting potential problems during process execution so that these problems can be proactively managed and mitigated.  ...  However, we lack empirical evidence to support this intuition, as research on predictive business process monitoring focused on aggregate prediction accuracy.  ...  Research leading to these results has received funding from the EFRE co-financed operational program NRW.Ziel2 under grant agreement 005-1010-0012 (LoFIP -Cockpits for Operational Management of Transport Processes  ... 
doi:10.1007/978-3-319-59536-8_28 fatcat:wdapzvmornfwrndievy37yil6i

Predictive Processing, Source Monitoring, and Psychosis

Juliet D. Griffin, Paul C. Fletcher
2017 Annual Review of Clinical Psychology  
We propose that the predictive processing framework has much to offer in this respect.  ...  Crucially, we see little conflict between source monitoring theories and predictive coding.  ...  How does Predictive Processing relate to Source Monitoring?  ... 
doi:10.1146/annurev-clinpsy-032816-045145 pmid:28375719 pmcid:PMC5424073 fatcat:764juqzl5veylpeovf467vxjpi

Clinical prediction in group psychotherapy

Christopher L. Chapman, Gary M. Burlingame, Robert Gleave, Frank Rees, Mark Beecher, Greg S. Porter
2012 Psychotherapy Research  
Clinical Prediction in Group Psychotherapy Christopher Chapman Department of Clinical Psychology Doctor of Philosophy Prior research in individual therapy has provided evidence that therapists are poor  ...  Therapists from a university counseling center and a state psychiatric hospital were recruited to test their accuracy in predicting client outcome, quality of therapeutic relationship and their own use  ...  as accurate, if not more accurate, than clinical prediction.  ... 
doi:10.1080/10503307.2012.702512 pmid:22775060 fatcat:rcvngpj2s5d7hmxi4ukzc7jezu

Heart Attack Prediction Using SMLT

E. Aloyses, C.Vidya Bhaskar, Soniya Priyatharsini. G, Ramesh Babu. V
2022 International journal of pharmaceutical sciences review and research  
Different algorithms are compared and the best model is used for predicting the outcome  ...  It associates many risk factors in heart disease and a need of the time to get accurate, reliable, and sensible approaches to make an early diagnosis to achieve prompt management of the disease.  ...  A validation dataset is a sample of data held back from training your model that is used to give an estimate of model skill while tuning models and procedures that you can use to make the best use of validation  ... 
doi:10.47583/ijpsrr.2022.v73i02.035 fatcat:q5dfvgbn5bduxcjbxrvvj4t2py

Prediction of the aging of polymer materials

E.V. Bystritskaya, A.L. Pomerantsev, O.Ye. Rodionova
1999 Chemometrics and Intelligent Laboratory Systems  
To receive the reliable forecast, it is necessary to use physically reasonable models of processes.  ...  The article deals with prediction of aging of multiplex polymer systems under conditions where the direct measurements of required properties are either impossible or difficult.  ...  The elementary method of stochastic approximation, where the linearization of model is used, does not give sufficient accuracy.  ... 
doi:10.1016/s0169-7439(98)00205-6 fatcat:jorwqxid6fbk5fazumygcpcvyy

Task predictability and remembered duration

Marilyn G. Boltz
1998 Perception & Psychophysics  
In each case, a higher degree of predictability led to more accurate and reliable duration estimates that were relatively free of bias, while uncertainty decreased accuracy through an overestimation bias  ...  The effects of structural predictability on remembered duration judgments were examined within the context of the performance of a series of highly familiar tasks.  ...  models would predict, but to shorter and more accurate estimates.  ... 
doi:10.3758/bf03206062 pmid:9682603 fatcat:svnyaepb5bacrmt6555la2jrnm

Continual-Learning-as-a-Service (CLaaS): On-Demand Efficient Adaptation of Predictive Models [article]

Rudy Semola, Vincenzo Lomonaco, Davide Bacciu
2022 arXiv   pre-print
Predictive machine learning models nowadays are often updated in a stateless and expensive way.  ...  The former is a robotic object recognition setting using the CORe50 dataset while the latter is a named category and attribute prediction using the DeepFashion-C dataset in the fashion domain.  ...  It is crucial to have a set of good evaluation metrics to monitor the model performance, i.e. the model forgets the past or does not learn new skills.  ... 
arXiv:2206.06957v2 fatcat:dbs7fmql6ffjppept27knysii4

Event Log Sampling for Predictive Monitoring [chapter]

Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan Johannes van Zelst, Wil M. P. van der Aalst
2022 Process Mining Workshops : ICPM 2021 International Workshops  
Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances.  ...  However, state-of-the-art methods for predictive monitoring require the training of complex machine learning models, which is often inefficient.  ...  Predictive business process monitoring aims at predicting the behavior of business processes, to mitigate the risk resulting from undesired behaviors in the process.  ... 
doi:10.18154/rwth-2022-04972 fatcat:ujzveju7nbhohe2j3av3l4pcoa

FragGeneScanRs: faster gene prediction for short reads

Felix Van der Jeugt, Peter Dawyndt, Bart Mesuere
2022 BMC Bioinformatics  
Results This paper introduces FragGeneScanRs, a faster Rust implementation of the FragGeneScan gene prediction model.  ...  Background FragGeneScan is currently the most accurate and popular tool for gene prediction in short and error-prone reads, but its execution speed is insufficient for use on larger data sets.  ...  In this manuscript we present FragGeneScanRs (FGSrs), a reliable, high-performance, and accurate Rust implementation of the FGS gene prediction model.  ... 
doi:10.1186/s12859-022-04736-5 pmid:35643462 pmcid:PMC9148508 fatcat:lorbnmnjlfezppp4wpozmgcxtm

Discussion: Prediction of Hyperbilirubinemia

Lois H Johnson, Chun B Chow
2001 Journal of Perinatology  
Although HPLC, in principle, is capable of giving more accurate measurements that the Ehrlich's diazo reaction, several HPLC methods are cited in the literature, many of which are not good.  ...  Infants whose levels are in the intermediate zone are monitored until the bilirubin level declines. DR. NEM-YUN BOO: The number of G6PD infants in your study was very small.  ... 
doi:10.1038/sj.jp.7210641 fatcat:wcmpl44d75bp7cu5dqflhq2bqq

Judicial Transparency in an Age of Prediction

Adam Samaha
2008 Social Science Research Network  
The Empirical Legal Studies (ELS) movement is making strides toward understanding judicial behavior, and ELS models could become the foundation for more accurate prediction of judicial decisions.  ...  First, what would an age of predictable judicial behavior look like? Second, would satisfying the informational needs of ELS prediction models also exhaust the demands for 'judicial transparency"?  ...  It does not add reasons to extract information from court systems beyond what is necessary to generate reliable models.  ... 
doi:10.2139/ssrn.1126404 fatcat:ryxsfqwwmzavtlzlt25v7p6bmu

What do predictive coders want?

Colin Klein
2016 Synthese  
The so-called "dark room problem" makes vivd the challenges that purely predictive models face in accounting for motivation. I argue that the problem is a serious one.  ...  The Free Energy principle might avoid the problem, but only at the cost of setting itself up as a highly idealized model, which is then literally false to the world.  ...  For helpful discussions, thanks to Esther Klein, Julia Staffel, Wolfgang Schwartz, the ANU 2013 reading group on predictive coding, and participants at the 2015 CAVE ""Predictive Coding, Delusions, and  ... 
doi:10.1007/s11229-016-1250-6 fatcat:eu5sqtdgdba5lmgixy6jho3vua

Review: Protein Secondary Structure Prediction Continues to Rise

Burkhard Rost
2001 Journal of Structural Biology  
, using hidden Markov models as input (12) ; SSpro, profilebased advanced neural network prediction method (13).  ...  , gapped and iterative specific profile-based, fast and accurate alignment method (10); PSIPRED, divergent profile (PSI-BLAST)-based neural network prediction (11); SAM-T99sec, neural network prediction  ...  The authors monitor regions for which secondary structure prediction methods give equally strong preferences for two different states.  ... 
doi:10.1006/jsbi.2001.4336 pmid:11551180 fatcat:rf2j4yf4xbdwtkkj7czcxeiyfm

Imagining Predictions: Mental Imagery as Mental Emulation [chapter]

Samuel T. Moulton, Stephen M. Kosslyn
2011 Predictions in the Brain  
Because a dot is by definition round, however, the roundness of your imaged dot hardly predicts anything. Now, what colour was your dot?  ...  Specifically, at this level, we ask: what mental structures and processes does imagery engage?  ... 
doi:10.1093/acprof:oso/9780195395518.003.0040 fatcat:yee4comod5hj5gfgszkxwfb3vy

Heart Disease Prediction System Using K- Nearest Neighbour Classification Technique

Sowbarnica V. S, Vismaya V, Vidhyapoonthalir M, S. Bhuvana
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
The existing system uses Support Vector Machine (SVM), it propose a system for heart disease prediction. The method will help doctor to explore their data and predict heart disease accurately.  ...  The heart is an operating system of the human body .If it does not function properly it will affect other parts also. Heart disease problem describes a range of conditions that affect your heart.  ...  The algorithm gives the nearby reliable outputs based on the input provided.  ... 
doi:10.32628/cseit195247 fatcat:lo7g6nziorgflkdahflnuy37qq
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