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https://www.readbyqxmd.com/read/28926310/coronary-ct-angiography-derived-fractional-flow-reserve
#1
Christian Tesche, Carlo N De Cecco, Moritz H Albrecht, Taylor M Duguay, Richard R Bayer, Sheldon E Litwin, Daniel H Steinberg, U Joseph Schoepf
Invasive coronary angiography (ICA) with measurement of fractional flow reserve (FFR) by means of a pressure wire technique is the established reference standard for the functional assessment of coronary artery disease (CAD) ( 1 , 2 ). Coronary computed tomographic (CT) angiography has emerged as a noninvasive method for direct assessment of CAD and plaque characterization with high diagnostic accuracy compared with ICA ( 3 , 4 ). However, the solely anatomic assessment provided with both coronary CT angiography and ICA has poor discriminatory power for ischemia-inducing lesions...
October 2017: Radiology
https://www.readbyqxmd.com/read/28923292/promising-non-pharmacological-therapies-in-pd-targeting-late-stage-disease-and-the-role-of-computer-based-cognitive-training
#2
S C F Van de Weijer, A L A J Hommel, B R Bloem, J Nonnekes, N M De Vries
Non-pharmacological interventions are increasingly being acknowledged as valuable treatment options to overcome or reduce functional problems in patients with Parkinson's disease (PD). There is a wide range of such non-pharmacological treatments for which the supportive evidence is emerging. Physiotherapy is one good example in this domain. However, there are also several promising non-pharmacological treatment strategies that have thus far received less research attention. Here, we describe two relatively new, but encouraging approaches...
September 4, 2017: Parkinsonism & related Disorders
https://www.readbyqxmd.com/read/28915974/rapid-and-accurate-intraoperative-pathological-diagnosis-by-artificial-intelligence-with-deep-learning-technology
#3
Jing Zhang, Yanlin Song, Fan Xia, Chenjing Zhu, Yingying Zhang, Wenpeng Song, Jianguo Xu, Xuelei Ma
Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm...
September 2017: Medical Hypotheses
https://www.readbyqxmd.com/read/28910867/-current-status-and-prospect-of-artificial-intelligence-in-pathology
#4
Y Xu, Y Tang, W Yan, Y Z Zhang, M D Lai
No abstract text is available yet for this article.
September 8, 2017: Zhonghua Bing Li Xue za Zhi Chinese Journal of Pathology
https://www.readbyqxmd.com/read/28906450/obstacle-recognition-based-on-machine-learning-for-on-chip-lidar-sensors-in-a-cyber-physical-system
#5
Fernando Castaño, Gerardo Beruvides, Rodolfo E Haber, Antonio Artuñedo
Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink...
September 14, 2017: Sensors
https://www.readbyqxmd.com/read/28903886/patient-privacy-in-the-era-of-big-data
#6
Mehmet Kayaalp
Privacy was defined as a fundamental human right in the Universal Declaration of Human Rights at the 1948 United Nations General Assembly. However, there is still no consensus on what constitutes privacy. In this review, we look at the evolution of privacy as a concept from the era of Hippocrates to the era of social media and big data. To appreciate the modern measures of patient privacy protection and correctly interpret the current regulatory framework in the United States, we need to analyze and understand the concepts of individually identifiable information, individually identifiable health information, protected health information (PHI), and de-identification...
September 13, 2017: Balkan Medical Journal
https://www.readbyqxmd.com/read/28893410/an-artificial-neural-network-to-predict-resting-energy-expenditure-in-obesity
#7
Emmanuel Disse, Séverine Ledoux, Cécile Bétry, Cyrielle Caussy, Christine Maitrepierre, Muriel Coupaye, Martine Laville, Chantal Simon
BACKGROUND & AIMS: The resting energy expenditure (REE) determination is important in nutrition for adequate dietary prescription. The gold standard i.e. indirect calorimetry is not available in clinical settings. Thus, several predictive equations have been developed, but they lack of accuracy in subjects with extreme weight including obese populations. Artificial neural networks (ANN) are useful predictive tools in the area of artificial intelligence, used in numerous clinical fields...
September 1, 2017: Clinical Nutrition: Official Journal of the European Society of Parenteral and Enteral Nutrition
https://www.readbyqxmd.com/read/28886480/intelligent-visual-localization-of-wireless-capsule-endoscopes-enhanced-by-color-information
#8
George Dimas, Evaggelos Spyrou, Dimitris K Iakovidis, Anastasios Koulaouzidis
Wireless capsule endoscopy (WCE) is performed with a miniature swallowable endoscope enabling the visualization of the whole gastrointestinal (GI) tract. One of the most challenging problems in WCE is the localization of the capsule endoscope (CE) within the GI lumen. Contemporary, radiation-free localization approaches are mainly based on the use of external sensors and transit time estimation techniques, with practically low localization accuracy. Latest advances for the solution of this problem include localization approaches based solely on visual information from the CE camera...
September 1, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28881183/from-machine-learning-to-deep-learning-progress-in-machine-intelligence-for-rational-drug-discovery
#9
REVIEW
Lu Zhang, Jianjun Tan, Dan Han, Hao Zhu
Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply...
September 4, 2017: Drug Discovery Today
https://www.readbyqxmd.com/read/28881099/renal-protective-and-ameliorating-impacts-of-omega-3-fatty-acids-against-aspartame-damaged-mdck-cells
#10
Muthuraman Pandurangan, Gansukh Enkhtaivan, Muthuviveganandavel Veerappan, Bhupendra Mistry, Rahul Patel, So Hyun Moon, Patnamsetty Chidanandha Nagajyothi, Doo Hwan Kim
Aspartame is widely used artificial sweeteners as food additives. Several researchers have pointed that the controversial report on the use of aspartame over more than decades. Omega-3 fatty acids are essential and unsaturated fatty acids, and it plays a remarkable role in vision, intelligence, neural development, and metabolism of neurotransmitters. Therefore, the present study was aimed to investigate the effect of omega-3 fatty acids on aspartame treated renal cells. Experimental groups were divided into three such as sham control, aspartame treated, and aspartame with omega-3 fatty acids...
September 7, 2017: BioFactors
https://www.readbyqxmd.com/read/28874806/self-powered-real-time-movement-monitoring-sensor-using-triboelectric-nanogenerator-technology
#11
Liangmin Jin, Juan Tao, Rongrong Bao, Li Sun, Caofeng Pan
The triboelectric nanogenerator (TENG) has great potential in the field of self-powered sensor fabrication. Recently, smart electronic devices and movement monitoring sensors have attracted the attention of scientists because of their application in the field of artificial intelligence. In this article, a TENG finger movement monitoring, self-powered sensor has been designed and analysed. Under finger movements, the TENG realizes the contact and separation to convert the mechanical energy into electrical signal...
September 5, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28872869/demystifying-multi-task-deep-neural-networks-for-quantitative-structure-activity-relationships
#12
Yuting Xu, Junshui Ma, Andy Liaw, Robert P Sheridan, Vladimir Svetnik
Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision and natural language processing. In the past four years, DNNs also generated promising results for quantitative structure-activity relationship (QSAR) tasks. Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR datasets. It was also found that multi-task DNN models - those trained on and predicting multiple QSAR properties simultaneously - outperform DNNs trained separately on the individual datasets in many but not all tasks...
September 5, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28870022/playing-to-our-human-strengths-to-prepare-medical-students-for-the-future
#13
Julie Chen
We are living in an age where artificial intelligence and astounding technological advances are bringing truly remarkable change to healthcare. Medical knowledge and skills which form the core responsibility of doctors such as making diagnoses may increasingly be delivered by robots. Machines are gradually acquiring human abilities such as deep learning and empathy. What, then is the role of doctors in future healthcare? And what direction should medical schools be taking to prepare their graduates? This article will give an overview of the evolving technological landscape of healthcare and examine the issues undergraduate medical education may have to address...
September 2017: Korean Journal of Medical Education
https://www.readbyqxmd.com/read/28864890/-computer-based-diagnosis-of-skin-cancer-using-artificial-intelligence
#14
F C Wolfsperger, A S Yazdi
No abstract text is available yet for this article.
September 1, 2017: Der Hautarzt; Zeitschrift Für Dermatologie, Venerologie, und Verwandte Gebiete
https://www.readbyqxmd.com/read/28864396/environmental-indicators-of-oyster-norovirus-outbreaks-in-coastal-waters
#15
Shima Shamkhali Chenar, Zhiqiang Deng
This paper presents an artificial intelligence-based approach to identifying environmental indicators of oyster norovirus outbreaks in coastal waters. It was found that oyster norovirus outbreaks are generally linked to the extreme combination of antecedent environmental conditions characterized by low water temperature, low solar radiation, low gage height, low salinity, strong wind, and heavy precipitation. Among the six environmental indicators, the most important three indicators, including water temperature, solar radiation and gage height, are capable of explaining 77...
August 25, 2017: Marine Environmental Research
https://www.readbyqxmd.com/read/28858309/artificial-intelligence-the-future-is-superintelligent
#16
Stuart Russell
No abstract text is available yet for this article.
August 30, 2017: Nature
https://www.readbyqxmd.com/read/28853856/highly-stretchable-ultrasensitive-and-wearable-strain-sensors-based-on-facilely-prepared-reduced-graphene-oxide-woven-fabrics-in-an-ethanol-flame
#17
Biao Yin, Yanwei Wen, Tao Hong, Zhongshuai Xie, Guoliang Yuan, Qingmin Ji, Hongbing Jia
The recent booming development of wearable electronics urgently calls for high-performance flexible strain sensors. To date, it is still a challenge to manufacture flexible strain sensors with superb sensitivity and a large workable strain range simultaneously. Herein, a facile, quick, cost-effective, and scalable strategy is adopted to fabricate novel strain sensors based on reduced graphene oxide woven fabrics (GWF). By pyrolyzing commercial cotton bandages coated with graphene oxide (GO) sheets in an ethanol flame, the reduction of GO and the pyrolysis of the cotton bandage template can be synchronously completed in tens of seconds...
September 11, 2017: ACS Applied Materials & Interfaces
https://www.readbyqxmd.com/read/28841437/new-insights-into-olivo-cerebellar-circuits-for-learning-from-a-small-training-sample
#18
REVIEW
Isao T Tokuda, Huu Hoang, Mitsuo Kawato
Artificial intelligence such as deep neural networks exhibited remarkable performance in simulated video games and 'Go'. In contrast, most humanoid robots in the DARPA Robotics Challenge fell down to ground. The dramatic contrast in performance is mainly due to differences in the amount of training data, which is huge and small, respectively. Animals are not allowed with millions of the failed trials, which lead to injury and death. Humans fall only several thousand times before they balance and walk. We hypothesize that a unique closed-loop neural circuit formed by the Purkinje cells, the cerebellar deep nucleus and the inferior olive in and around the cerebellum and the highest density of gap junctions, which regulate synchronous activities of the inferior olive nucleus, are computational machinery for learning from a small sample...
August 19, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28841416/high-definition-medicine
#19
REVIEW
Ali Torkamani, Kristian G Andersen, Steven R Steinhubl, Eric J Topol
The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution-what we refer to as high-definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging, and behavioral tracking. Our ability to understand and act upon these observations at equally high precision is driven by advances in genome editing, cellular reprogramming, tissue engineering, and information technologies, especially artificial intelligence...
August 24, 2017: Cell
https://www.readbyqxmd.com/read/28840365/radiology-and-enterprise-medical-imaging-extensions-remix
#20
Barbaros S Erdal, Luciano M Prevedello, Songyue Qian, Mutlu Demirer, Kevin Little, John Ryu, Thomas O'Donnell, Richard D White
Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence...
August 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
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