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https://www.readbyqxmd.com/read/28423745/reasoning-and-data-representation-in-a-health-and-lifestyle-support-system
#1
Sten Hanke, Karl Kreiner, Johannes Kropf, Marc Scase, Christian Gossy
Case-based reasoning and data interpretation is an artificial intelligence approach that capitalizes on past experience to solve current problems and this can be used as a method for practical intelligent systems. Case-based data reasoning is able to provide decision support for experts and clinicians in health systems as well as lifestyle systems. In this project we were focusing on developing a solution for healthy ageing considering daily activities, nutrition as well as cognitive activities. The data analysis of the reasoner followed state of the art guidelines from clinical practice...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28382802/major-clinical-research-advances-in-gynecologic-cancer-in-2016-10-year-special-edition
#2
REVIEW
Dong Hoon Suh, Miseon Kim, Kidong Kim, Hak Jae Kim, Kyung Hun Lee, Jae Weon Kim
In 2016, 13 topics were selected as major research advances in gynecologic oncology. For ovarian cancer, study results supporting previous ones regarding surgical preventive strategies were reported. There were several targeted agents that showed comparable responses in phase III trials, including niraparib, cediranib, and nintedanib. On the contrary to our expectations, dose-dense weekly chemotherapy regimen failed to prove superior survival outcomes compared with conventional triweekly regimen. Single-agent non-platinum treatment to prolong platinum-free-interval in patients with recurrent, partially platinum-sensitive ovarian cancer did not improve and even worsened overall survival (OS)...
May 2017: Journal of Gynecologic Oncology
https://www.readbyqxmd.com/read/28373615/the-co-existence-of-technology-and-caring-in-the-theory-of-technological-competency-as-caring-in-nursing
#3
Rozzano C Locsin
The coexistence of technology and caring is best exemplified in nursing. The theory of Technological Competency as Caring in Nursing illuminates this coexistence as the essence of technology in health care premised on machine technologies as a generic concept of objects or things that are mechanical, organic, and electronic. With its timely development these technologies are continually imbued with artificial general intelligence. As such, the ultimate expression of machine technologies in nursing turns out to be autonomous robots (ARs) with future potentials of functions comparable to human persons...
2017: Journal of Medical Investigation: JMI
https://www.readbyqxmd.com/read/28353110/heavy-metal-monitoring-analysis-and-prediction-in-lakes-and-rivers-state-of-the-art
#4
Adnan Elzwayie, Haitham Abdulmohsin Afan, Mohammed Falah Allawi, Ahmed El-Shafie
Several research efforts have been conducted to monitor and analyze the impact of environmental factors on the heavy metal concentrations and physicochemical properties of water bodies (lakes and rivers) in different countries worldwide. This article provides a general overview of the previous works that have been completed in monitoring and analyzing heavy metals. The intention of this review is to introduce the historical studies to distinguish and understand the previous challenges faced by researchers in analyzing heavy metal accumulation...
March 29, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28341861/minimum-vertex-type-sequence-indexing-for-clusters-on-square-lattice
#5
Longguang Liao, Yu-Jun Zhao, Zexian Cao, Xiao-Bao Yang
An effective indexing scheme for clusters that enables fast structure comparison and congruence check is desperately desirable in the field of mathematics, artificial intelligence, materials science, etc. Here we introduce the concept of minimum vertex-type sequence for the indexing of clusters on square lattice, which contains a series of integers each labeling the vertex type of an atom. The minimum vertex-type sequence is orientation independent, and it builds a one-to-one correspondence with the cluster...
March 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28325604/early-prediction-of-radiotherapy-induced-parotid-shrinkage-and-toxicity-based-on-ct-radiomics-and-fuzzy-classification
#6
Marco Pota, Elisa Scalco, Giuseppe Sanguineti, Alessia Farneti, Giovanni Mauro Cattaneo, Giovanna Rizzo, Massimo Esposito
MOTIVATION: Patients under radiotherapy for head-and-neck cancer often suffer of long-term xerostomia, and/or consistent shrinkage of parotid glands. In order to avoid these drawbacks, adaptive therapy can be planned for patients at risk, if the prediction is obtained timely, before or during the early phase of treatment. Artificial intelligence can address the problem, by learning from examples and building classification models. In particular, fuzzy logic has shown its suitability for medical applications, in order to manage uncertain data, and to build transparent rule-based classifiers...
March 18, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28325441/a-review-of-fuzzy-cognitive-maps-in-medicine-taxonomy-methods-and-applications
#7
REVIEW
Abdollah Amirkhani, Elpiniki I Papageorgiou, Akram Mohseni, Mohammad R Mosavi
BACKGROUND AND OBJECTIVE: A high percentage of medical errors, committed because of physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to medical records of previous patients, can be reduced using computer-aided techniques. Therefore, designing more efficient medical decision-support systems (MDSSs) to assist physicians in decision-making is crucially important. Through combining the properties of fuzzy logic and neural networks, fuzzy cognitive maps (FCMs) are among the latest, most efficient, and strongest artificial intelligence techniques for modeling complex systems...
April 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28298701/identification-of-probabilities
#8
Paul M B Vitányi, Nick Chater
Within psychology, neuroscience and artificial intelligence, there has been increasing interest in the proposal that the brain builds probabilistic models of sensory and linguistic input: that is, to infer a probabilistic model from a sample. The practical problems of such inference are substantial: the brain has limited data and restricted computational resources. But there is a more fundamental question: is the problem of inferring a probabilistic model from a sample possible even in principle? We explore this question and find some surprisingly positive and general results...
February 2017: Journal of Mathematical Psychology
https://www.readbyqxmd.com/read/28254495/an-artificial-intelligence-framework-for-compensating-transgressions-and-its-application-to-diet-management
#9
Luca Anselma, Alessandro Mazzei, Franco De Michieli
Today, there is considerable interest in personal healthcare. The pervasiveness of technology allows to precisely track human behavior; however, when dealing with the development of an intelligent assistant exploiting data acquired through such technologies, a critical issue has to be taken into account; namely, that of supporting the user in the event of any transgression with respect to the optimal behavior. In this paper we present a reasoning framework based on Simple Temporal Problems that can be applied to a general class of problems,, which we called "cake&carrot problems", to support reasoning in presence of human transgression...
February 27, 2017: Journal of Biomedical Informatics
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
#10
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/28138223/computational-intelligence-models-to-predict-porosity-of-tablets-using-minimum-features
#11
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/28126242/artificial-intelligence-in-medicine
#12
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...
April 2017: Metabolism: Clinical and Experimental
https://www.readbyqxmd.com/read/28117445/dermatologist-level-classification-of-skin-cancer-with-deep-neural-networks
#13
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
#14
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/28110106/fast-learning-method-for-convolutional-neural-networks-using-extreme-learning-machine-and-its-application-to-lane-detection
#15
Jihun Kim, Jonghong Kim, Gil-Jin Jang, Minho Lee
Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection...
March 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28002840/suprasegmental-characteristics-of-spontaneous-speech-produced-in-good-and-challenging-communicative-conditions-by-talkers-aged-9-14-years
#16
Valerie Hazan, Outi Tuomainen, Michèle Pettinato
Purpose: This study investigated the acoustic characteristics of spontaneous speech by talkers aged 9-14 years and their ability to adapt these characteristics to maintain effective communication when intelligibility was artificially degraded for their interlocutor. Method: Recordings were made for 96 children (50 female participants, 46 male participants) engaged in a problem-solving task with a same-sex friend; recordings for 20 adults were used as reference. The task was carried out in good listening conditions (normal transmission) and in degraded transmission conditions...
December 1, 2016: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/27996165/mimicking-classical-conditioning-based-on-a-single-flexible-memristor
#17
Chaoxing Wu, Tae Whan Kim, Tailiang Guo, Fushan Li, Dea Uk Lee, J Joshua Yang
The mimicking of classical conditioning, including acquisition, extinction, recovery, and generalization, can be efficiently achieved by using a single flexible memristor. In particular, the experiment of Pavlov's dog is successfully demonstrated. This demonstration paves the way for reproducing advanced neural processes and provides a frontier approach to the design of artificial intelligence systems with dramatically reduced complexity.
December 20, 2016: Advanced Materials
https://www.readbyqxmd.com/read/27919375/software-intelligent-system-for-effective-solutions-for-hearing-impaired-subjects
#18
Rajkumar S, Muttan S, Sapthagirivasan V, Jaya V, Vignesh S S
PURPOSE: The anatomy and physiology of the ear is complex in nature, which makes it a challenge for audiologists to prescribe solutions for varied hearing-impaired subjects. There is a need to increase the satisfaction level of hearing-aid users by adopting better strategies that involve modern technological advancements. AIM: To design and develop a decision support Software Intelligent System (SIS) that performs audiological investigations to assess the degree of hearing loss and to suggest appropriate hearing-aid gain values...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27881212/building-machines-that-learn-and-think-like-people
#19
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman
Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it...
November 24, 2016: Behavioral and Brain Sciences
https://www.readbyqxmd.com/read/27830257/public-health-and-epidemiology-informatics
#20
A Flahault, A Bar-Hen, N Paragios
OBJECTIVES: The aim of this manuscript is to provide a brief overview of the scientific challenges that should be addressed in order to unlock the full potential of using data from a general point of view, as well as to present some ideas that could help answer specific needs for data understanding in the field of health sciences and epidemiology. METHODS: A survey of uses and challenges of big data analyses for medicine and public health was conducted. The first part of the paper focuses on big data techniques, algorithms, and statistical approaches to identify patterns in data...
November 10, 2016: Yearbook of Medical Informatics
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