Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU

Machine learning approaches have been effective in predicting adverse outcomes in different clinical settings. These models are often developed and evaluated on datasets with heterogeneous patient populations. However, good predictive performance on the aggregate population does not imply good performance for specific groups. In this work, we present a two-step framework to 1) learn relevant patient subgroups, and 2) predict an outcome for separate patient populations in a multi-task framework, where each population is a separate task. We demonstrate how to discover relevant groups in an unsupervised way with a sequence-to-sequence autoencoder. We show that using these groups in a multi-task framework leads to better predictive performance of in-hospital mortality both across groups and overall. We also highlight the need for more granular evaluation of performance when dealing with heterogeneous populations.Comment: KDD 201

Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues

Toward the automation of business process ontology generation

Semantic Business Process Management (SBPM) utilises semantic technologies (e.g., ontology) to model and query process representations. There are times in which such models must be reconstructed from existing textual documentation. In this scenario the automated generation of ontological models would be preferable, however current methods and technology are still not capable of automatically generating accurate semantic process models from textual descriptions. This research attempts to automate the process as much as possible by proposing a method that drives the transformation through the joint use of a foundational ontology and lexico-semantic analysis. The method is presented, demonstrated and evaluated. The original dataset represents 150 business activities related to the procurement processes of a case study company. As the evaluation shows, the proposed method can accurately map the linguistic patterns of the process descriptions to semantic patterns of the foundational ontology to a high level of accuracy, however further research is required in order to reduce the level of human intervention, expand the method so as to recognise further patterns of the foundational ontology and develop a tool to assist the business process modeller in the semi-automated generation of process models

Can biological quantum networks solve NP-hard problems?

There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines. During the last decades the question has therefore been raised whether we need to consider quantum effects to explain the imagined cognitive power of a conscious mind. This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness and cognition. The purpose is to be able to identify and evaluate instances where quantum effects might play a significant role in cognitive processes. Not surprisingly, the conclusion is that quantum-enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence the functionality of various components and signalling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. So, the conclusion is that biological quantum networks can only approximately solve small instances of NP-hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to efficiently solve NP-hard problems approximately. In the end it is a question of precision - Nature is approximate.Comment: 38 page

Becoming a Home-Educator in a Networked World: Towards the Democratisation of Education Alternatives?

The internet is assumed to play a special role for Elective Home Education (EHE) in the UK and has anecdotally fuelled an increase in its prevalence. Yet little is known about the how the internet features in experiences of discovering EHE. This study reports on the ways in which a predominantly middle-class and highly educated faction have appropriated the internet to develop networks and communities to support the informational, social and emotional needs of new families. The research formed part of a mixed-method doctoral study that included: an online survey of 242 home-educators; 52 individual and group interviews with 85 parents, children and young people and a week-long participant observation with families. In the absence of any "official discourse" for them, initiating contact with existing home-educators online socialised prospective families into a normalised "Do It Yourself" education culture. However, access was a complex achievement that predicated the demonstration of allegiances and commitment. The modalities of power mirrored online left some families on the periphery indefinitely, while others used the internet to cultivate self-selecting communities elsewhere. The conclusions paint a paradoxical picture for the illusive promise of the democratisation of education

Innovation driven sectoral shocks and aggregate city cycles

This paper formalizes one mechanism through which diversification in the production of research & development across firms located in a city dampens volatility in the local labor market, improves the incentives to perform research & development and smooths the aggregate business cycle fluctuations of a city. This is done by adapting the standard multi-sector quality ladder model (Grossman and Helpman 1991) in order to allow for heterogeneity across firms, thus taking into account knowledge spillovers across heterogenous sectors, knowledge accumulation, pecuniary externalities and segmented labor markets. As a result, according to the local degree of diversification in research & development, sectoral technological shocks have an influence on the current choice of research & development and the location of production, and in turn on local business cycles and the life cycle of the city: diversification in research & development allows innovations in different sectors of the city to arrive at different points in time, thus avoiding to put pressure on the local labor markets and keeping wage discipline. This permits firms located in the city to perform enough research & development and possibly beat outside competition in discovering and manufacturing new products, thus growing -at the aggregate city level-through less volatile cycles.quality ladder with heterogeneity across firms, labor pooling economies, knowledge spillovers, diversification, schumpeterian growth in the city