keyword
MENU ▼
Read by QxMD icon Read
search

artificial intelligence

keyword
https://www.readbyqxmd.com/read/29155645/from-images-to-actions-opportunities-for-artificial-intelligence-in-radiology
#1
Charles E Kahn
No abstract text is available yet for this article.
December 2017: Radiology
https://www.readbyqxmd.com/read/29155639/when-machines-think-radiology-s-next-frontier
#2
Keith J Dreyer, J Raymond Geis
Artificial intelligence (AI), machine learning, and deep learning are terms now seen frequently, all of which refer to computer algorithms that change as they are exposed to more data. Many of these algorithms are surprisingly good at recognizing objects in images. The combination of large amounts of machine-consumable digital data, increased and cheaper computing power, and increasingly sophisticated statistical models combine to enable machines to find patterns in data in ways that are not only cost-effective but also potentially beyond humans' abilities...
December 2017: Radiology
https://www.readbyqxmd.com/read/29152886/a-contrast-based-computational-model-of-surprise-and-its-applications
#3
Luis Macedo, Amílcar Cardoso
We review our work on a contrast-based computational model of surprise and its applications. The review is contextualized within related research from psychology, philosophy, and particularly artificial intelligence. Influenced by psychological theories of surprise, the model assumes that surprise-eliciting events initiate a series of cognitive processes that begin with the appraisal of the event as unexpected, continue with the interruption of ongoing activity and the focusing of attention on the unexpected event, and culminate in the analysis and evaluation of the event and the revision of beliefs...
November 19, 2017: Topics in Cognitive Science
https://www.readbyqxmd.com/read/29147562/cognitive-computing-and-escience-in-health-and-life-science-research-artificial-intelligence-and-obesity-intervention-programs
#4
REVIEW
Thomas Marshall, Tiffiany Champagne-Langabeer, Darla Castelli, Deanna Hoelscher
Objective: To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. Methods: The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience...
December 2017: Health Information Science and Systems
https://www.readbyqxmd.com/read/29144420/visual-positioning-indoors-human-eyes-vs-smartphone-cameras
#5
Dewen Wu, Ruizhi Chen, Liang Chen
Artificial Intelligence (AI) technologies and their related applications are now developing at a rapid pace. Indoor positioning will be one of the core technologies that enable AI applications because people spend 80% of their time indoors. Humans can locate themselves related to a visually well-defined object, e.g., a door, based on their visual observations. Can a smartphone camera do a similar job when it points to an object? In this paper, a visual positioning solution was developed based on a single image captured from a smartphone camera pointing to a well-defined object...
November 16, 2017: Sensors
https://www.readbyqxmd.com/read/29141699/the-chimes-of-freedom
#6
John Harris
This essay brings together work I have done over the past 10 years: on the nature of ethics, on the purpose of ethics, and on its foundations in a way that, I hope, as E.M. Forster put it, connects "the prose and the passion." I deploy lessons learned in this process to identify and face what I believe to be crucial challenges to science and to freedom (as defended by, among others, Cicero, Pete Seeger, Bob Dylan, Thomas Hobbes, John Stuart Mill, and Bertrand Russell). Finally I consider threats to freedom of a different sort, posed by the creation and dissemination of "alternative facts" and by what is sometimes called "super" or "full" artificial intelligence (AI)...
November 16, 2017: Cambridge Quarterly of Healthcare Ethics: CQ: the International Journal of Healthcare Ethics Committees
https://www.readbyqxmd.com/read/29139385/-the-potential-of-artificial-intelligence-in-myology-a-viewpoint-from-a-non-robot
#7
Eytan Beckmann, Bruno Peyrou, Laure Gallay, Jean-Jacques Vignaux
No abstract text is available yet for this article.
November 2017: Médecine Sciences: M/S
https://www.readbyqxmd.com/read/29137456/highly-stretchable-conductors-based-on-expanded-graphite-macro-confined-in-tubular-rubber
#8
Wei Luo, Tongfei Wu, Biqiong Chen, Mei Liang, Huawei Zou
Highly stretchable and durable conductors are significant to the development of wearable devices, robots, human-machine interfaces and other artificial intelligence products. Although many respectable methods have been reported, it is still a challenge to fabricate stretchable conductors with a large elastic limit, high conductivity and excellent reliability in rapid, effective and economic ways. Herein, a facile method is offered to fabricate high-performance stretchable tubular conductors (TCs) based on a macro-confined structure of expanded graphite (EG) in rubber tubing by simply physical packing...
November 15, 2017: ACS Applied Materials & Interfaces
https://www.readbyqxmd.com/read/29134342/an-introduction-and-overview-of-machine-learning-in-neurosurgical-care
#9
REVIEW
Joeky T Senders, Mark M Zaki, Aditya V Karhade, Bliss Chang, William B Gormley, Marike L Broekman, Timothy R Smith, Omar Arnaout
BACKGROUND: Machine learning (ML) is a branch of artificial intelligence that allows computers to learn from large complex datasets without being explicitly programmed. Although ML is already widely manifest in our daily lives in various forms, the considerable potential of ML has yet to find its way into mainstream medical research and day-to-day clinical care. The complex diagnostic and therapeutic modalities used in neurosurgery provide a vast amount of data that is ideally suited for ML models...
November 13, 2017: Acta Neurochirurgica
https://www.readbyqxmd.com/read/29134320/artificial-intelligence-in-neurodegenerative-disease-research-use-of-ibm-watson-to-identify-additional-rna-binding-proteins-altered-in-amyotrophic-lateral-sclerosis
#10
Nadine Bakkar, Tina Kovalik, Ileana Lorenzini, Scott Spangler, Alix Lacoste, Kyle Sponaugle, Philip Ferrante, Elenee Argentinis, Rita Sattler, Robert Bowser
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with no effective treatments. Numerous RNA-binding proteins (RBPs) have been shown to be altered in ALS, with mutations in 11 RBPs causing familial forms of the disease, and 6 more RBPs showing abnormal expression/distribution in ALS albeit without any known mutations. RBP dysregulation is widely accepted as a contributing factor in ALS pathobiology. There are at least 1542 RBPs in the human genome; therefore, other unidentified RBPs may also be linked to the pathogenesis of ALS...
November 13, 2017: Acta Neuropathologica
https://www.readbyqxmd.com/read/29129011/embodiment-and-estrangement-results-from-first-in-human-intelligent-bci-trial
#11
F Gilbert, M Cook, T O'Brien, J Illes
While new generations of implantable brain computer interface (BCI) devices are being developed, evidence in the literature about their impact on the patient experience is lagging. In this article, we address this knowledge gap by analysing data from the first-in-human clinical trial to study patients with implanted BCI advisory devices. We explored perceptions of self-change across six patients who volunteered to be implanted with artificially intelligent BCI devices. We used qualitative methodological tools grounded in phenomenology to conduct in-depth, semi-structured interviews...
November 11, 2017: Science and Engineering Ethics
https://www.readbyqxmd.com/read/29127485/oct-based-deep-learning-algorithm-for-the-evaluation-of-treatment-indication-with-anti-vascular-endothelial-growth-factor-medications
#12
Philipp Prahs, Viola Radeck, Christian Mayer, Yordan Cvetkov, Nadezhda Cvetkova, Horst Helbig, David Märker
PURPOSE: Intravitreal injections with anti-vascular endothelial growth factor (anti-VEGF) medications have become the standard of care for their respective indications. Optical coherence tomography (OCT) scans of the central retina provide detailed anatomical data and are widely used by clinicians in the decision-making process of anti-VEGF indication. In recent years, significant progress has been made in artificial intelligence and computer vision research. We trained a deep convolutional artificial neural network to predict treatment indication based on central retinal OCT scans without human intervention...
November 10, 2017: Graefe's Archive for Clinical and Experimental Ophthalmology
https://www.readbyqxmd.com/read/29126825/artificial-intelligence-in-medical-practice-the-question-to-the-answer
#13
REVIEW
D Douglas Miller, Eric W Brown
Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society - forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence...
November 7, 2017: American Journal of Medicine
https://www.readbyqxmd.com/read/29124837/synthetic-ion-channels-and-dna-logic-gates-as-components-of-molecular-robots
#14
Ryuji Kawano
A molecular robot is a next-generation biological robot consisting of biomaterials such as DNA, proteins, and lipids that imitates the actions of microorganisms. Three prerequisites have been proposed for the construction of such a robot: sensor, intelligence, and actuator. This minireview focuses on recent research on synthetic ion channels and DNA computing technologies, which are viewed as potential candidate components of molecular robots. Synthetic ion channels, which are embedded in an artificial cell membrane (lipid bilayer), sense ambient ions or chemicals and incorporate the molecules...
November 9, 2017: Chemphyschem: a European Journal of Chemical Physics and Physical Chemistry
https://www.readbyqxmd.com/read/29117716/artificial-intelligence-magic-l-intelligence-artificielle-de-la-magie
#15
Kirk Barber
No abstract text is available yet for this article.
November 2017: Journal of Cutaneous Medicine and Surgery
https://www.readbyqxmd.com/read/29117178/predictable-response-finding-optimal-drugs-and-doses-using-artificial-intelligence
#16
Shraddha Chakradhar
No abstract text is available yet for this article.
November 7, 2017: Nature Medicine
https://www.readbyqxmd.com/read/29112973/reading-wild-minds-a-computational-assay-of-theory-of-mind-sophistication-across-seven-primate-species
#17
Marie Devaine, Aurore San-Galli, Cinzia Trapanese, Giulia Bardino, Christelle Hano, Michel Saint Jalme, Sebastien Bouret, Shelly Masi, Jean Daunizeau
Theory of Mind (ToM), i.e. the ability to understand others' mental states, endows humans with highly adaptive social skills such as teaching or deceiving. Candidate evolutionary explanations have been proposed for the unique sophistication of human ToM among primates. For example, the Machiavellian intelligence hypothesis states that the increasing complexity of social networks may have induced a demand for sophisticated ToM. This type of scenario ignores neurocognitive constraints that may eventually be crucial limiting factors for ToM evolution...
November 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/29109070/artificial-intelligence-learning-semantics-via-external-resources-for-classifying-diagnosis-codes-in-discharge-notes
#18
Chin Lin, Chia-Jung Hsu, Yu-Sheng Lou, Shih-Jen Yeh, Chia-Cheng Lee, Sui-Lung Su, Hsiang-Cheng Chen
BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). OBJECTIVE: Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes...
November 6, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/29106268/strategy-selection-as-rational-metareasoning
#19
Falk Lieder, Thomas L Griffiths
Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question of how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy's performance...
November 2017: Psychological Review
https://www.readbyqxmd.com/read/29105694/-handle-with-care-about-the-potential-unintended-consequences-of-oracular-artificial-intelligence-systems-in-medicine
#20
Federico Cabitza, Camilla Alderighi, Raffaele Rasoini, Gian Franco Gensini
Decisional support systems based on machine learning (ML) in medicine are gaining a growing interest as some recent articles have highlighted the high diagnostic accuracy exhibited by these systems in specific medical contexts. However, it is implausible that any potential advantage can be obtained without some potential drawbacks. In light of the current gaps in medical research about the side effects of the application of these new AI systems in medical practice, in this article we summarize the main unexpected consequences that may result from the widespread application of "oracular" systems, that is highly accurate systems that cannot give reasonable explanations of their advice as those endowed with predictive models developed with ML techniques usually are...
October 2017: Recenti Progressi in Medicina
keyword
keyword
6207
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"