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https://www.readbyqxmd.com/read/28210230/acute-mental-discomfort-associated-with-suicide-behavior-in-a-clinical-sample-of-patients-with-affective-disorders-ascertaining-critical-variables-using-artificial-intelligence-tools
#1
Susana Morales, Jorge Barros, Orietta Echávarri, Fabián García, Alex Osses, Claudia Moya, María Paz Maino, Ronit Fischman, Catalina Núñez, Tita Szmulewicz, Alemka Tomicic
AIM: In efforts to develop reliable methods to detect the likelihood of impending suicidal behaviors, we have proposed the following. OBJECTIVE: To gain a deeper understanding of the state of suicide risk by determining the combination of variables that distinguishes between groups with and without suicide risk. METHOD: A study involving 707 patients consulting for mental health issues in three health centers in Greater Santiago, Chile. Using 345 variables, an analysis was carried out with artificial intelligence tools, Cross Industry Standard Process for Data Mining processes, and decision tree techniques...
2017: Frontiers in Psychiatry
https://www.readbyqxmd.com/read/28209428/an-artificial-intelligence-based-improved-classification-of-two-phase-flow-patterns-with-feature-extracted-from-acquired-images
#2
C Shanthi, N Pappa
Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing...
February 13, 2017: ISA Transactions
https://www.readbyqxmd.com/read/28198674/sequence-specific-bias-correction-for-rna-seq-data-using-recurrent-neural-networks
#3
Yao-Zhong Zhang, Rui Yamaguchi, Seiya Imoto, Satoru Miyano
BACKGROUND: The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures...
January 25, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28197092/bci-control-of-heuristic-search-algorithms
#4
Marc Cavazza, Gabor Aranyi, Fred Charles
The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users' mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28182259/artificial-intelligence-ai-systems-for-interpreting-complex-medical-data-sets
#5
Russ B Altman
Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence applications in medical data have several technical challenges: complex and heterogeneous data sets, noisy medical data sets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics and liability...
February 9, 2017: Clinical Pharmacology and Therapeutics
https://www.readbyqxmd.com/read/28176905/effect-of-roll-compaction-on-granule-size-distribution-of-microcrystalline-cellulose-mannitol-mixtures-computational-intelligence-modeling-and-parametric-analysis
#6
Pezhman Kazemi, Mohammad Hassan Khalid, Ana Pérez Gago, Peter Kleinebudde, Renata Jachowicz, Jakub Szlęk, Aleksander Mendyk
Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD) and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD...
2017: Drug Design, Development and Therapy
https://www.readbyqxmd.com/read/28174613/banknote-recognition-investigating-processing-and-cognition-framework-using-competitive-neural-network
#7
Oyebade K Oyedotun, Adnan Khashman
Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded...
February 2017: Cognitive Neurodynamics
https://www.readbyqxmd.com/read/28167793/theory-of-cortical-function
#8
David J Heeger
Most models of sensory processing in the brain have a feedforward architecture in which each stage comprises simple linear filtering operations and nonlinearities. Models of this form have been used to explain a wide range of neurophysiological and psychophysical data, and many recent successes in artificial intelligence (with deep convolutional neural nets) are based on this architecture. However, neocortex is not a feedforward architecture. This paper proposes a first step toward an alternative computational framework in which neural activity in each brain area depends on a combination of feedforward drive (bottom-up from the previous processing stage), feedback drive (top-down context from the next stage), and prior drive (expectation)...
February 6, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28160385/processing-binary-and-fuzzy-logic-by-chaotic-time-series-generated-by-a-hydrodynamic-photochemical-oscillator
#9
Pier Luigi Gentili, Maria Sole Giubila, B Mark Heron
This work demonstrates the computational power of a hydrodynamic photochemical oscillator based on a photochromic naphthopyran, generating aperiodic time series. The chaotic character of the time series is tested by calculating its largest Lyapunov exponent and the correlation dimension of its attractor after building its phase space through the Takens' theorem. Then, the chaotic dynamic is shown to be suitable to implement all the fundamental Boolean two-inputs-one-output logic gates. Finally, the strategy to implement Fuzzy logic systems (FLSs) based on the time series is described...
February 3, 2017: Chemphyschem: a European Journal of Chemical Physics and Physical Chemistry
https://www.readbyqxmd.com/read/28160296/in-defense-of-artificial-replacement
#10
Derek Shiller
If it is within our power to provide a significantly better world for future generations at a comparatively small cost to ourselves, we have a strong moral reason to do so. One way of providing a significantly better world may involve replacing our species with something better. It is plausible that in the not-too-distant future, we will be able to create artificially intelligent creatures with whatever physical and psychological traits we choose. Granted this assumption, it is argued that we should engineer our extinction so that our planet's resources can be devoted to making artificial creatures with better lives...
February 3, 2017: Bioethics
https://www.readbyqxmd.com/read/28159597/gene-selection-for-microarray-cancer-classification-using-a-new-evolutionary-method-employing-artificial-intelligence-concepts
#11
M Dashtban, Mohammadali Balafar
Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators...
January 31, 2017: Genomics
https://www.readbyqxmd.com/read/28147292/comparing-strengths-and-weaknesses-of-three-ecosystem-services-modelling-tools-in-a-diverse-uk-river-catchment
#12
Katrina Sharps, Dario Masante, Amy Thomas, Bethanna Jackson, John Redhead, Linda May, Havard Prosser, Bernard Cosby, Bridget Emmett, Laurence Jones
Ecosystem services modelling tools can help land managers and policy makers evaluate the impacts of alternative management options or changes in land use on the delivery of ecosystem services. As the variety and complexity of these tools increases, there is a need for comparative studies across a range of settings, allowing users to make an informed choice. Using examples of provisioning and regulating services (water supply, carbon storage and nutrient retention), we compare three spatially explicit tools - LUCI (Land Utilisation and Capability Indicator), ARIES (Artificial Intelligence for Ecosystem Services) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs)...
January 29, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28140632/what-is-morphological-computation-on-how-the-body-contributes-to-cognition-and-control
#13
Vincent C Müller, Matej Hoffmann
The contribution of the body to cognition and control in natural and artificial agents is increasingly described as "offloading computation from the brain to the body," where the body is said to perform "morphological computation." Our investigation of four characteristic cases of morphological computation in animals and robots shows that the "offloading" perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word...
January 31, 2017: Artificial Life
https://www.readbyqxmd.com/read/28138223/computational-intelligence-models-to-predict-porosity-of-tablets-using-minimum-features
#14
Mohammad Hassan Khalid, Pezhman Kazemi, Lucia Perez-Gandarillas, Abderrahim Michrafy, Jakub Szlęk, Renata Jachowicz, Aleksander Mendyk
The effects of different formulations and manufacturing process conditions on the physical properties of a solid dosage form are of importance to the pharmaceutical industry. It is vital to have in-depth understanding of the material properties and governing parameters of its processes in response to different formulations. Understanding the mentioned aspects will allow tighter control of the process, leading to implementation of quality-by-design (QbD) practices. Computational intelligence (CI) offers an opportunity to create empirical models that can be used to describe the system and predict future outcomes in silico...
2017: Drug Design, Development and Therapy
https://www.readbyqxmd.com/read/28134366/materials-learning-from-life-concepts-for-active-adaptive-and-autonomous-molecular-systems
#15
REVIEW
Rémi Merindol, Andreas Walther
Bioinspired out-of-equilibrium systems will set the scene for the next generation of molecular materials with active, adaptive, autonomous, emergent and intelligent behavior. Indeed life provides the best demonstrations of complex and functional out-of-equilibrium systems: cells keep track of time, communicate, move, adapt, evolve and replicate continuously. Stirred by the understanding of biological principles, artificial out-of-equilibrium systems are emerging in many fields of soft matter science. Here we put in perspective the molecular mechanisms driving biological functions with the ones driving synthetic molecular systems...
January 30, 2017: Chemical Society Reviews
https://www.readbyqxmd.com/read/28131438/-artificial-intelligence-in-the-field-of-internal-medicine
#16
L Chiche, H Servy
No abstract text is available yet for this article.
January 25, 2017: La Revue de Médecine Interne
https://www.readbyqxmd.com/read/28126242/artificial-intelligence-in-medicine
#17
Pavel Hamet, Johanne Tremblay
Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation...
January 11, 2017: Metabolism: Clinical and Experimental
https://www.readbyqxmd.com/read/28117445/dermatologist-level-classification-of-skin-cancer-with-deep-neural-networks
#18
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, Sebastian Thrun
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs...
February 2, 2017: Nature
https://www.readbyqxmd.com/read/28113586/a-robust-approach-for-the-background-subtraction-based-on-multi-layered-self-organizing-maps
#19
Giorgio Gemignani, Alessandro Rozza
Motion detection in video streams is a challenging task for several computer vision applications. Indeed, segmentation of moving and static elements in the scene allows to increase the efficiency of several challenging tasks such as human computer interface (HCI), robot visions, and intelligent surveillance systems. In this paper, we approach motion detection through a multilayered artificial neural network, which is able to build for each background pixel a multi-modal color distribution evolving over time through self organization...
August 31, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28111297/modeling-of-glucose-release-from-native-and-modified-wheat-starch-gels-during-in-vitro-gastrointestinal-digestion-using-artificial-intelligence-methods
#20
A R Yousefi, Seyed M A Razavi
Estimation of the amounts of glucose release (AGR) during gastrointestinal digestion can be useful to identify food of potential use in the diet of individuals with diabetes. In this work, adaptive neuro-fuzzy inference system (ANFIS), genetic algorithm-artificial neural network (GA-ANN) and group method of data handling (GMDH) models were applied to estimate the AGR from native (NWS), cross-linked (CLWS) and hydroxypropylated wheat starch (HPWS) gels during digestion under simulated gastrointestinal conditions...
April 2017: International Journal of Biological Macromolecules
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