Patient Engagement: Theoretical and Heuristic Approaches for Supporting the Clinical Practice.

Social interaction allows to support the disease management by creating online spaces where patients can interact with clinicians, and share experiences with other patients. Therefore, promoting targeted communication in online social spaces is a mean to group patients around shared goals, offer emotional support, and finally engage patients in their healthcare decision-making process. In this paper, we approach the argument from a theoretical perspective: we design an optimization problem aimed to encourage the creation of (induced) sub-networks of patients which, being recently diagnosed, wish to deepen the knowledge about their medical treatment with some other similar profiled patients, which have already been followed up by specific (even alternative) care centers. In particular, due to the computational hardness of the proposed problem, we provide approximated solutions based on distributed heuristics (i.e., Genetic Algorithms). Results are given for simulated data using Erdös-Rényi random graphs.

[1]  Jessica Andrea Carballido,et al.  On Stopping Criteria for Genetic Algorithms , 2004, SBIA.

[2]  E. Coiera.  Social networks, social media, and social diseases , 2013, BMJ.

[3]  Petr A. Golovach,et al.  Finding clubs in graph classes , 2014, Discret. Appl. Math..

[4]  Yuichi Asahiro,et al.  Approximating Maximum Diameter-Bounded Subgraphs , 2010, LATIN.

[5]  David E. Goodrich,et al.  An Online Community Improves Adherence in an Internet-Mediated Walking Program. Part 1: Results of a Randomized Controlled Trial , 2010, Journal of medical Internet research.

[6]  Giancarlo Mauri,et al.  DIABESITY: A Study for mHealth Integrated Solutions , 2016, MobiHealth.

[7]  Gilbert Laporte,et al.  An exact algorithm for the maximum k-club problem in an undirected graph , 1999, Eur. J. Oper. Res..

[8]  Maw-Shang Chang,et al.  Finding large $$k$$-clubs in undirected graphs , 2013, Computing.

[9]  Lee Altenberg,et al.  The Schema Theorem and Price's Theorem , 1994, FOGA.

[10]  R. J. Mokken,et al.  Cliques, clubs and clans , 1979 .

[11]  L. Mirny,et al.  Protein complexes and functional modules in molecular networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Srinivas Pasupuleti,et al.  Detection of Protein Complexes in Protein Interaction Networks Using n-Clubs , 2008, EvoBIO.

[13]  R. J. Mokken,et al.  Close communication and 2-clubs in corporate networks: Europe 2010 , 2015, Social Network Analysis and Mining.

[14]  Christian Komusiewicz,et al.  Multivariate Algorithmics for Finding Cohesive Subnetworks , 2016, Algorithms.

[15]  Riccardo Dondi,et al.  Clique Editing to Support Case Versus Control Discrimination , 2016, KES-IDT.

[16]  Rich Caruana,et al.  Removing the Genetics from the Standard Genetic Algorithm , 1995, ICML.

[17]  Gary D. Bader,et al.  An automated method for finding molecular complexes in large protein interaction networks , 2003, BMC Bioinformatics.

[18]  Christopher E. Beaudoin,et al.  Modeling the impact of online cancer resources on supporters of cancer patients , 2008, New Media Soc..

[19]  R. Alba.  A graph‐theoretic definition of a sociometric clique† , 1973 .

[20]  Riccardo Dondi,et al.  Orthology Correction for Gene Tree Reconstruction: Theoretical and Experimental Results , 2017, ICCS.

[21]  Maarten Marx,et al.  Close communities in social networks: boroughs and 2-clubs , 2015, Social Network Analysis and Mining.

[22]  Christian Komusiewicz,et al.  An algorithmic framework for fixed-cardinality optimization in sparse graphs applied to dense subgraph problems , 2015, Discret. Appl. Math..

[23]  Luca Scrucca,et al.  GA: A Package for Genetic Algorithms in R , 2013 .

[24]  Jean-Philippe Rennard,et al.  Stochastic Optimization Algorithms , 2007, ArXiv.

[25]  Raymond Chiong,et al.  Why Is Optimization Difficult? , 2009, Nature-Inspired Algorithms for Optimisation.

[26]  Béla Bollobás,et al.  Random Graphs , 1985 .

[27]  Sergiy Butenko,et al.  Novel Approaches for Analyzing Biological Networks , 2005, J. Comb. Optim..

[28]  Christian Komusiewicz,et al.  Parameterized Algorithmics and Computational Experiments for Finding 2-Clubs , 2015, J. Graph Algorithms Appl..

[29]  Christian Komusiewicz,et al.  Parameterized computational complexity of finding small-diameter subgraphs , 2012, Optim. Lett..

[30]  Giancarlo Mauri,et al.  Social media and mobile applications in chronic disease prevention and management , 2015, Front. Psychol..

[31]  Roded Sharan,et al.  Center CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis , 2000, ISMB.

[32]  Atsushi Tsuya,et al.  Do Cancer Patients Tweet? Examining the Twitter Use of Cancer Patients in Japan , 2014, Journal of medical Internet research.

[33]  Stephen R. Marsland,et al.  Convergence Properties of (μ + λ) Evolutionary Algorithms , 2011, AAAI.