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https://www.readbyqxmd.com/read/29448930/a-prediction-study-of-warfarin-individual-stable-dose-after-mechanical-heart-valve-replacement-adaptive-neural-fuzzy-inference-system-prediction
#1
Huan Tao, Qian Li, Qin Zhou, Jie Chen, Bo Fu, Jing Wang, Wenzhe Qin, Jianglong Hou, Jin Chen, Li Dong
BACKGROUND: It's difficult but urgent to achieve the individualized rational medication of the warfarin, we aim to predict the individualized warfarin stable dose though the artificial intelligent Adaptive neural-fuzzy inference system (ANFIS). METHODS: Our retrospective analysis based on a clinical database, involving 21,863 patients from 15 Chinese provinces who receive oral warfarin after the heart valve replacement. They were allocated into four groups: the external validation group (A group), the internal validation group (B group), training group (C group) and stratified training group (D group)...
February 15, 2018: BMC Surgery
https://www.readbyqxmd.com/read/29385749/a-brief-review-of-facial-emotion-recognition-based-on-visual-information
#2
Byoung Chul Ko
Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms...
January 30, 2018: Sensors
https://www.readbyqxmd.com/read/29378578/artificial-intelligence-on-the-identification-of-risk-groups-for-osteoporosis-a-general-review
#3
REVIEW
Agnaldo S Cruz, Hertz C Lins, Ricardo V A Medeiros, José M F Filho, Sandro G da Silva
INTRODUCTION: The goal of this paper is to present a critical review on the main systems that use artificial intelligence to identify groups at risk for osteoporosis or fractures. The systems considered for this study were those that fulfilled the following requirements: range of coverage in diagnosis, low cost and capability to identify more significant somatic factors. METHODS: A bibliographic research was done in the databases, PubMed, IEEExplorer Latin American and Caribbean Center on Health Sciences Information (LILACS), Medical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, Web of Science, and Science Direct searching the terms "Neural Network", "Osteoporosis Machine Learning" and "Osteoporosis Neural Network"...
January 29, 2018: Biomedical Engineering Online
https://www.readbyqxmd.com/read/29375975/computational-intelligence-assisted-understanding-of-nature-inspired-superhydrophobic-behavior
#4
Xia Zhang, Bei Ding, Ran Cheng, Sebastian C Dixon, Yao Lu
In recent years, state-of-the-art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature-inspired superhydrophobic behavior...
January 2018: Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
https://www.readbyqxmd.com/read/29346328/comparison-of-svm-rf-and-elm-on-an-electronic-nose-for-the-intelligent-evaluation-of-paraffin-samples
#5
Hong Men, Songlin Fu, Jialin Yang, Meiqi Cheng, Yan Shi, Jingjing Liu
Paraffin odor intensity is an important quality indicator when a paraffin inspection is performed. Currently, paraffin odor level assessment is mainly dependent on an artificial sensory evaluation. In this paper, we developed a paraffin odor analysis system to classify and grade four kinds of paraffin samples. The original feature set was optimized using Principal Component Analysis (PCA) and Partial Least Squares (PLS). Support Vector Machine (SVM), Random Forest (RF), and Extreme Learning Machine (ELM) were applied to three different feature data sets for classification and level assessment of paraffin...
January 18, 2018: Sensors
https://www.readbyqxmd.com/read/29339817/cooperating-with-machines
#6
Jacob W Crandall, Mayada Oudah, Tennom, Fatimah Ishowo-Oloko, Sherief Abdallah, Jean-François Bonnefon, Manuel Cebrian, Azim Shariff, Michael A Goodrich, Iyad Rahwan
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultural norms, emotions, signals, and pre-evolved dispositions...
January 16, 2018: Nature Communications
https://www.readbyqxmd.com/read/29319225/de-novo-design-of-bioactive-small-molecules-by-artificial-intelligence
#7
Daniel Merk, Lukas Friedrich, Francesca Grisoni, Gisbert Schneider
Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model...
January 10, 2018: Molecular Informatics
https://www.readbyqxmd.com/read/29306756/a-loop-based-neural-architecture-for-structured-behavior-encoding-and-decoding
#8
Thomas Gisiger, Mounir Boukadoum
We present a new type of artificial neural network that generalizes on anatomical and dynamical aspects of the mammal brain. Its main novelty lies in its topological structure which is built as an array of interacting elementary motifs shaped like loops. These loops come in various types and can implement functions such as gating, inhibitory or executive control, or encoding of task elements to name a few. Each loop features two sets of neurons and a control region, linked together by non-recurrent projections...
December 8, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29305341/a-pilot-study-of-biomedical-text-comprehension-using-an-attention-based-deep-neural-reader-design-and-experimental-analysis
#9
Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, Jaewoo Kang
BACKGROUND: With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain...
January 5, 2018: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29224260/-ten-years-retrospective-review-of-the-application-of-digital-medical-technology-in-general-surgery-in-china
#10
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
#11
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
#12
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
#13
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
#14
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
#15
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
#16
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
#17
Dileep George, Wolfgang Lehrach, Ken Kansky, Miguel Lázaro-Gredilla, Christopher Laan, Bhaskara Marthi, Xinghua Lou, Zhaoshi Meng, Yi Liu, Huayan Wang, Alex Lavin, D Scott Phoenix
Learning from a few examples and generalizing to markedly 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...
December 8, 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
#18
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
#19
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...
February 2018: Advances in Neonatal Care: Official Journal of the National Association of Neonatal Nurses
https://www.readbyqxmd.com/read/28980130/artificial-intelligence-in-cardiology
#20
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...
December 2017: Wiener Klinische Wochenschrift
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