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https://www.readbyqxmd.com/read/29224260/-ten-years-retrospective-review-of-the-application-of-digital-medical-technology-in-general-surgery-in-china
#1
C H Fang, Y Y Lau, W P Zhou, W Cai
Digital medical technology is a powerful tool which has forcefully promoted the development of general surgery in China. In this article, we reviews the application status of three-dimensional visualization and three-dimensional printing technology in general surgery, introduces the development situation of surgical navigation guided by optical and electromagnetic technology and preliminary attempt to combined with mixed reality applied to complicated hepatectomy, looks ahead the development direction of digital medicine in the era of artificial intelligence and big data on behalf of surgical robot and radiomics...
December 1, 2017: Zhonghua Wai Ke za Zhi [Chinese Journal of Surgery]
https://www.readbyqxmd.com/read/29188913/-a-new-artificial-intelligence-tool-for-assessing-symptoms-in-patients-seeking-emergency-department-care-the-mediktor-application
#2
Elvira Moreno Barriga, Irene Pueyo Ferrer, Miquel Sánchez Sánchez, Montserrat Martín Baranera, Josep Masip Utset
OBJECTIVES: To analyze agreement between diagnoses issued by the Mediktor application and those of an attending physician, and to evaluate the usefulness of this application in patients who seek emergency care. MATERIAL AND METHODS: Prospective observational study in a tertiary care university hospital emergency department. Patients with medical problems and surgical conditions (surgery and injuries) who did not require immediate emergency care responded to the Mediktor questions on a portable computer tablet...
2017: Emergencias: Revista de la Sociedad Española de Medicina de Emergencias
https://www.readbyqxmd.com/read/29155639/when-machines-think-radiology-s-next-frontier
#3
REVIEW
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/29112973/reading-wild-minds-a-computational-assay-of-theory-of-mind-sophistication-across-seven-primate-species
#4
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
#5
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/29089575/projective-simulation-with-generalization
#6
Alexey A Melnikov, Adi Makmal, Vedran Dunjko, Hans J Briegel
The ability to generalize is an important feature of any intelligent agent. Not only because it may allow the agent to cope with large amounts of data, but also because in some environments, an agent with no generalization capabilities cannot learn. In this work we outline several criteria for generalization, and present a dynamic and autonomous machinery that enables projective simulation agents to meaningfully generalize. Projective simulation, a novel, physical approach to artificial intelligence, was recently shown to perform well in standard reinforcement learning problems, with applications in advanced robotics as well as quantum experiments...
October 31, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29089551/nature-of-collective-decision-making-by-simple-yes-no-decision-units
#7
Eisuke Hasegawa, Nobuaki Mizumoto, Kazuya Kobayashi, Shigeto Dobata, Jin Yoshimura, Saori Watanabe, Yuuka Murakami, Kenji Matsuura
The study of collective decision-making spans various fields such as brain and behavioural sciences, economics, management sciences, and artificial intelligence. Despite these interdisciplinary applications, little is known regarding how a group of simple 'yes/no' units, such as neurons in the brain, can select the best option among multiple options. One prerequisite for achieving such correct choices by the brain is correct evaluation of relative option quality, which enables a collective decision maker to efficiently choose the best option...
October 31, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29074582/a-generative-vision-model-that-trains-with-high-data-efficiency-and-breaks-text-based-captchas
#8
D George, W Lehrach, K Kansky, M Lázaro-Gredilla, C Laan, B Marthi, X Lou, Z Meng, Y Liu, H Wang, A Lavin, D S Phoenix
Learning from few examples and generalizing to dramatically different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems neuroscience, we introduce a probabilistic generative model for vision in which message-passing based inference handles recognition, segmentation and reasoning in a unified way. The model demonstrates excellent generalization and occlusion-reasoning capabilities, and outperforms deep neural networks on a challenging scene text recognition benchmark while being 300-fold more data efficient...
October 26, 2017: Science
https://www.readbyqxmd.com/read/29066576/real-time-differentiation-of-adenomatous-and-hyperplastic-diminutive-colorectal-polyps-during-analysis-of-unaltered-videos-of-standard-colonoscopy-using-a-deep-learning-model
#9
Michael F Byrne, Nicolas Chapados, Florian Soudan, Clemens Oertel, Milagros Linares Pérez, Raymond Kelly, Nadeem Iqbal, Florent Chandelier, Douglas K Rex
BACKGROUND: In general, academic but not community endoscopists have demonstrated adequate endoscopic differentiation accuracy to make the 'resect and discard' paradigm for diminutive colorectal polyps workable. Computer analysis of video could potentially eliminate the obstacle of interobserver variability in endoscopic polyp interpretation and enable widespread acceptance of 'resect and discard'. STUDY DESIGN AND METHODS: We developed an artificial intelligence (AI) model for real-time assessment of endoscopic video images of colorectal polyps...
October 24, 2017: Gut
https://www.readbyqxmd.com/read/29045255/listening-to-relaxing-music-improves-physiological-responses-in-premature-infants-a-randomized-controlled-trial
#10
Rafael A Caparros-Gonzalez, Alejandro de la Torre-Luque, Carolina Diaz-Piedra, Francisco J Vico, Gualberto Buela-Casal
BACKGROUND: Premature infants are exposed to high levels of noise in the neonatal intensive care unit (NICU). PURPOSE: This study evaluated the effect of a relaxing music therapy intervention composed by artificial intelligence on respiratory rate, systolic and diastolic blood pressure, and heart rate. METHODS: A double-blind, randomized, controlled trial was conducted in the NICUs of 2 general public hospitals in Andalusia, Spain. Participants were 17 healthy premature infants, randomly allocated to the intervention group or the control group (silence) at a 1:1 ratio...
October 17, 2017: Advances in Neonatal Care: Official Journal of the National Association of Neonatal Nurses
https://www.readbyqxmd.com/read/28980130/artificial-intelligence-in-cardiology
#11
REVIEW
Diana Bonderman
Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general...
October 4, 2017: Wiener Klinische Wochenschrift
https://www.readbyqxmd.com/read/28903886/patient-privacy-in-the-era-of-big-data
#12
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/28864396/environmental-indicators-of-oyster-norovirus-outbreaks-in-coastal-waters
#13
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/28814023/representing-high-dimensional-data-to-intelligent-prostheses-and-other-wearable-assistive-robots-a-first-comparison-of-tile-coding-and-selective-kanerva-coding
#14
Jaden B Travnik, Patrick M Pilarski
Prosthetic devices have advanced in their capabilities and in the number and type of sensors included in their design. As the space of sensorimotor data available to a conventional or machine learning prosthetic control system increases in dimensionality and complexity, it becomes increasingly important that this data be represented in a useful and computationally efficient way. Well structured sensory data allows prosthetic control systems to make informed, appropriate control decisions. In this study, we explore the impact that increased sensorimotor information has on current machine learning prosthetic control approaches...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28791547/data-based-prediction-of-blood-glucose-concentrations-using-evolutionary-methods
#15
J Ignacio Hidalgo, J Manuel Colmenar, Gabriel Kronberger, Stephan M Winkler, Oscar Garnica, Juan Lanchares
Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections...
August 8, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28678162/monitoring-based-model-for-personalizing-the-clinical-process-of-crohn-s-disease
#16
Alberto de Ramón-Fernández, Daniel Ruiz-Fernández, Diego Marcos-Jorquera, Virgilio Gilart-Iglesias, Víctor Vives-Boix
Crohn's disease is a chronic pathology belonging to the group of inflammatory bowel diseases. Patients suffering from Crohn's disease must be supervised by a medical specialist for the rest of their lives; furthermore, each patient has its own characteristics and is affected by the disease in a different way, so health recommendations and treatments cannot be generalized and should be individualized for a specific patient. To achieve this personalization in a cost-effective way using technology, we propose a model based on different information flows: control, personalization, and monitoring...
July 5, 2017: Sensors
https://www.readbyqxmd.com/read/28663789/molecular-and-phenotypic-biomarkers-of-aging
#17
REVIEW
Xian Xia, Weiyang Chen, Joseph McDermott, Jing-Dong Jackie Han
Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging are valuable tools to measure physiological age, assess the extent of 'healthy aging', and potentially predict health span and life span for an individual. Given the complex nature of the aging process, the biomarkers of aging are multilayered and multifaceted. Here, we review the phenotypic and molecular biomarkers of aging. Identifying and using biomarkers of aging to improve human health, prevent age-associated diseases, and extend healthy life span are now facilitated by the fast-growing capacity of multilevel cross-sectional and longitudinal data acquisition, storage, and analysis, particularly for data related to general human populations...
2017: F1000Research
https://www.readbyqxmd.com/read/28634156/classifying-chinese-questions-related-to-health-care-posted-by-consumers-via-the-internet
#18
Haihong Guo, Xu Na, Li Hou, Jiao Li
BACKGROUND: In question answering (QA) system development, question classification is crucial for identifying information needs and improving the accuracy of returned answers. Although the questions are domain-specific, they are asked by non-professionals, making the question classification task more challenging. OBJECTIVE: This study aimed to classify health care-related questions posted by the general public (Chinese speakers) on the Internet. METHODS: A topic-based classification schema for health-related questions was built by manually annotating randomly selected questions...
June 20, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28566328/somatic-mutations-drive-distinct-imaging-phenotypes-in-lung-cancer
#19
Emmanuel Rios Velazquez, Chintan Parmar, Ying Liu, Thibaud P Coroller, Gisele Cruz, Olya Stringfield, Zhaoxiang Ye, Mike Makrigiorgos, Fiona Fennessy, Raymond H Mak, Robert Gillies, John Quackenbush, Hugo J W L Aerts
Tumors are characterized by somatic mutations that drive biological processes ultimately reflected in tumor phenotype. With regard to radiographic phenotypes, generally unconnected through present understanding to the presence of specific mutations, artificial intelligence methods can automatically quantify phenotypic characters by using predefined, engineered algorithms or automatic deep-learning methods, a process also known as radiomics. Here we demonstrate how imaging phenotypes can be connected to somatic mutations through an integrated analysis of independent datasets of 763 lung adenocarcinoma patients with somatic mutation testing and engineered CT image analytics...
July 15, 2017: Cancer Research
https://www.readbyqxmd.com/read/28537378/self-healing-highly-sensitive-electronic-sensors-enabled-by-metal-ligand-coordination-and-hierarchical-structure-design
#20
Yangyang Han, Xiaodong Wu, Xinxing Zhang, Canhui Lu
Electronic sensors capable of capturing mechanical deformation are highly desirable for the next generation of artificial intelligence products. However, it remains a challenge to prepare self-healing, highly sensitive, and cost-efficient sensors for both tiny and large human motion monitoring. Here, a new kind of self-healing, sensitive, and versatile strain sensors has been developed by combining metal-ligand chemistry with hierarchical structure design. Specifically, a self-healing and nanostructured conductive layer is deposited onto a self-healing elastomer substrate cross-linked by metal-ligand coordinate bonds, forming a hierarchically structured sensor...
June 1, 2017: ACS Applied Materials & Interfaces
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