A frame reduction system based on a color structural similarity (CSS) method and Bayer images analysis for capsule endoscopy
Publication date: Available online 29 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Qasim Al-sheban, Prashan Premaratne, Darryl J. McAndrew, Peter J. Vial, Shehan AbeyAbstractA capsule endoscopy examination of the human small bowel generates a large number of images that have high similarity. In order to reduce the time it takes to review the high similarity images, clinicians will increase the playback speed, typically to 15 frames per second [1]. Associated with this behaviour is an increased probability of overlooking an image that may contain an abnormality. An alternative option to increasing the ...
Source: Artificial Intelligence in Medicine - December 30, 2018 Category: Bioinformatics Source Type: research

Project INSIDE: towards autonomous semi-unstructured human–robot social interaction in autism therapy
Publication date: Available online 28 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Francisco S. Melo, Alberto Sardinha, David Belo, Marta Couto, Miguel Faria, Anabela Farias, Hugo Gambôa, Cátia Jesus, Mithun Kinarullathil, Pedro Lima, Luís Luz, André Mateus, Isabel Melo, Plinio Moreno, Daniel Osório, Ana Paiva, Jhielson Pimentel, João Rodrigues, Pedro Sequeira, Rubén Solera-UreñaAbstractThis paper describes the INSIDE system, a networked robot system designed to allow the use of mobile robots as active players in the therapy of children with autis...
Source: Artificial Intelligence in Medicine - December 29, 2018 Category: Bioinformatics Source Type: research

Profiling continuous sleep representations for better understanding of the dynamic character of normal sleep
Publication date: Available online 29 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Zuzana Roštáková, Roman RosipalAbstractThe amount and quality of sleep substantially influence health, daily behaviour and overall quality of life. The main goal of this study was to investigate to what extent sleep structure derived from polysomnographic (PSG) recordings of nocturnal human sleep can provide information about sleep quality in terms of correlation with a set of variables representing daytime subjective, neurophysiological and cognitive states of a healthy population without serious s...
Source: Artificial Intelligence in Medicine - December 29, 2018 Category: Bioinformatics Source Type: research

A novel dynamical approach in continuous cuffless blood pressure estimation based on ECG and PPG signals
Publication date: Available online 23 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Iman Sharifi, Sobhan Goudarzi, Mohammad Bagher KhodabakhshiAbstractContinuous cuffless blood pressure (BP) monitoring has attracted much interest in finding the ideal treatment of diseases and the prevention of premature death. This paper presents a novel dynamical method, based on pulse transit time (PTT) and photoplethysmogram intensity ratio (PIR), for the continuous cuffless BP estimation. By taking the advantages of both the modeling and the prediction approaches, the proposed framework effectively estimates diasto...
Source: Artificial Intelligence in Medicine - December 24, 2018 Category: Bioinformatics Source Type: research

BDI personal medical assistant agents: The case of trauma tracking and alerting
Publication date: Available online 20 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Angelo Croatti, Sara Montagna, Alessandro Ricci, Emiliano Gamberini, Vittorio Albarello, Vanni AgnolettiAbstractPersonal assistant agents can have an important role in healthcare as a smart technology to support physicians in their daily work, helping to tackle the increasing complexity of their task environment. In this paper we present and discuss a personal medical assistant agent technology for trauma documentation and management, based on the Belief-Desire-Intention (BDI) architecture. The purpose of the personal a...
Source: Artificial Intelligence in Medicine - December 20, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: November 2018Source: Artificial Intelligence in Medicine, Volume 92Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 18, 2018 Category: Bioinformatics Source Type: research

Fuzzy logic based approaches for gene regulatory network inference
Publication date: Available online 17 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Khalid RazaAbstractThe rapid advancements in high-throughput techniques have fueled large-scale production of biological data at very affordable costs. Some of these techniques are microarrays and next-generation sequencing that provide genome level insight of living cells. As a result, the size of most of the biological databases, such as NCBI-GEO, NCBI-SRA, etc., is growing exponentially. These biological data are analyzed using various computational techniques for knowledge discovery – which is also one of the ...
Source: Artificial Intelligence in Medicine - December 18, 2018 Category: Bioinformatics Source Type: research

CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm
Publication date: Available online 14 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Ahmed M. Anter, Aboul Ella HassenianAbstractLiver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the liver with the same intensity, high noise and large variance of tumors. The segmentation process is necessary for the detection, identification, and measurement of objects in CT images. We perform an extensive review of the CT liver segmentation literature. Furthermore, in this paper, an improved segmenta...
Source: Artificial Intelligence in Medicine - December 15, 2018 Category: Bioinformatics Source Type: research

Optimal testing policies for diagnosing patients with intermediary probability of disease
Publication date: Available online 5 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Edilson F. Arruda, Basílio B. Pereira, Clarissa A. Thiers, Bernardo R. TuraAbstractThis paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach derives an optimal policy whereby the decision maker is provided with a test strategy...
Source: Artificial Intelligence in Medicine - December 6, 2018 Category: Bioinformatics Source Type: research

An efficient and fast computer-aided method for fully automated diagnosis of meniscal tears from magnetic resonance images
This study proposes a novel three-stage (preprocessing, segmentation and classification) method for fully automated classification from MR images, and shows the performance of each stage separately. At the preprocessing step, the most compact rectangular windows for the menisci were obtained from MR slices. At the segmentation step, the menisci were segmented using fuzzy clustering methods. In order to classify the segmented images and to determine meniscus tears, three different classifiers were used. The method first decides whether there are tears on menisci; if this is the case then, determines the place and type of th...
Source: Artificial Intelligence in Medicine - December 5, 2018 Category: Bioinformatics Source Type: research

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome
Publication date: Available online 28 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Mireia Calvo, Virginie Le Rolle, Daniel Romero, Nathalie Béhar, Pedro Gomis, Philippe Mabo, Alfredo I. HernándezAbstractThis paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a ...
Source: Artificial Intelligence in Medicine - November 30, 2018 Category: Bioinformatics Source Type: research

A computer-aided diagnosis system for HEp-2 fluorescence intensity classification
ConclusionsThe results confirm the effectiveness of our proposal, also revealing that it achieves the same performance as medical experts. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 28, 2018 Category: Bioinformatics Source Type: research

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification
Publication date: Available online 23 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Imon Banerjee, Yuan Ling, Matthew C. Chen, Sadid A. Hasan, Curtis P. Langlotz, Nathaniel Moradzadeh, Brian Chapman, Timothy Amrhein, David Mong, Daniel L. Rubin, Oladimeji Farri, Matthew P. LungrenAbstractThis paper explores cutting-edge deep learning methods for information extraction from medical imaging free text reports at a multi-institutional scale and compares them to the state-of-the-art domain-specific rule-based system – PEFinder and traditional machine learning methods – SVM and Adaboost. We propo...
Source: Artificial Intelligence in Medicine - November 24, 2018 Category: Bioinformatics Source Type: research

Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning
Publication date: Available online 23 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Juan Fdez-Olivares, Eva Onaindia, Luis Castillo, Jaume Jordán, Juan CózarAbstractThe conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized conciliation of multiple guidelines considering additionally patient preferences brings some further difficulties. Recently, several works have explored distinct techniques to come up...
Source: Artificial Intelligence in Medicine - November 23, 2018 Category: Bioinformatics Source Type: research

Diabetic retinopathy techniques in retinal images: A review
Publication date: Available online 16 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Nadeem Salamat, Malik M. Saad Missen, Aqsa RashidAbstractThe diabetic retinopathy is the main reason of vision loss in people. Medical experts recognize some clinical, geometrical and haemodynamic features of diabetic retinopathy. These features include the blood vessel area, exudates, microaneurysm, hemorrhages and neovascularization, etc. In Computer Aided Diagnosis (CAD) systems, these features are detected in fundus images using computer vision techniques. In this paper, we review the methods of low, middle and high...
Source: Artificial Intelligence in Medicine - November 16, 2018 Category: Bioinformatics Source Type: research

Indexing the Event Calculus: Towards practical human-readable Personal Health Systems
Publication date: Available online 13 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Nicola Falcionelli, Paolo Sernani, Albert Brugués, Dagmawi Neway Mekuria, Davide Calvaresi, Michael Schumacher, Aldo Franco Dragoni, Stefano BromuriAbstractPersonal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of events: for example, in Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitor...
Source: Artificial Intelligence in Medicine - November 14, 2018 Category: Bioinformatics Source Type: research

Neural network modelling of soft tissue deformation for surgical simulation
Publication date: Available online 13 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Jinao Zhang, Yongmin Zhong, Chengfan GuAbstractThis paper presents a new neural network methodology for modelling of soft tissue deformation for surgical simulation. The proposed methodology formulates soft tissue deformation and its dynamics as the neural propagation and dynamics of cellular neural networks for real-time, realistic, and stable simulation of soft tissue deformation. It develops two cellular neural network models; based on the bioelectric propagation of biological tissues and principles of continuum mech...
Source: Artificial Intelligence in Medicine - November 14, 2018 Category: Bioinformatics Source Type: research

Segmentation of breast MR images using a generalised 2D mathematical model with inflation and deflation forces of active contours
The objective of the study is to develop a fully automated method for breast and pectoral muscle boundary estimation in MR images. Firstly, we develop a 2D breast mathematical model based on 30 MRI slices (from a patient) and identify important landmarks to obtain a model for the general shape of the breast in an axial plane. Subsequently, we use Otsu's thresholding approach and Canny edge detection to estimate the breast boundary. The active contour method is then employed using both inflation and deflation forces to estimate the pectoral muscle boundary by taking account of information obtained from the proposed 2D model...
Source: Artificial Intelligence in Medicine - November 11, 2018 Category: Bioinformatics Source Type: research

Computational normalization of H&E-stained histological images: Progress, challenges and future potential
Publication date: Available online 9 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Thaína A. Azevedo Tosta, Paulo Rogério de Faria, Leandro Alves Neves, Marcelo Zanchetta do NascimentoAbstractDifferent types of cancer can be diagnosed with the analysis of histological samples stained with hematoxylin–eosin (H&E). Through this stain, it is possible to identify the architecture of tissue components and analyze cellular morphological aspects that are essential for cancer diagnosis. However, preparation and digitization of histological samples can lead to color variations that influ...
Source: Artificial Intelligence in Medicine - November 11, 2018 Category: Bioinformatics Source Type: research

Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks
ConclusionOur proposed computational model accurately predicts the outcome of blood culture tests using nine clinical parameters. Moreover, it can be used in the ICU as an early warning system to detect patients at risk of blood stream infection. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 11, 2018 Category: Bioinformatics Source Type: research

Computational methods for Gene Regulatory Networks reconstruction and analysis: A review
Publication date: Available online 9 November 2018Source: Artificial Intelligence in MedicineAuthor(s): Fernando M. Delgado, Francisco Gómez-VelaAbstractIn the recent years, the vast amount of genetic information generated by new-generation approaches, have led to the need of new data handling methods. The integrative analysis of diverse-nature gene information could provide a much-sought overview to study complex biological systems and processes. In this sense, Gene Regulatory Networks (GRN) arise as an increasingly-promising tool for the modelling and analysis of biological processes. This review is an attempt to ...
Source: Artificial Intelligence in Medicine - November 11, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: September 2018Source: Artificial Intelligence in Medicine, Volume 91Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 7, 2018 Category: Bioinformatics Source Type: research

Preface: AIME 2017
Publication date: September 2018Source: Artificial Intelligence in Medicine, Volume 91Author(s): Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 7, 2018 Category: Bioinformatics Source Type: research

Towards automatic encoding of medical procedures using convolutional neural networks and autoencoders
Publication date: Available online 29 October 2018Source: Artificial Intelligence in MedicineAuthor(s): Yihan Deng, André Sander, Lukas Faulstich, Kerstin DeneckeAbstractClassification systems such as ICD-10 for diagnoses or the Swiss Operation Classification System (CHOP) for procedure classification in the clinical treatment are essential for clinical management and information exchange. Traditionally, classification codes are assigned manually or by systems that rely upon concept-based or rule-based classification methods. Such methods can reach their limit easily due to the restricted coverage of handcrafted rul...
Source: Artificial Intelligence in Medicine - October 30, 2018 Category: Bioinformatics Source Type: research

Arden Syntax: Then, now, and in the future
Publication date: Available online 25 October 2018Source: Artificial Intelligence in MedicineAuthor(s): Klaus-Peter Adlassnig, Peter Haug, Robert A. Jenders (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 26, 2018 Category: Bioinformatics Source Type: research

On predicting epithelial mesenchymal transition by integrating RNA-binding proteins and correlation data via L1/2-regularization method
Publication date: Available online 21 October 2018Source: Artificial Intelligence in MedicineAuthor(s): Yushan Qiu, Hao Jiang, Wai-Ki Ching, Michael K. NgAbstractIdentifying tumor metastasis signatures from gene expression data at the whole genome level remains an arduous challenge, particularly so when the number of genes is huge and the number of experimental samples is small. We focus on the prediction of the epithelial-mesenchymal transition (EMT), which is an underlying mechanism of tumor metastasis, here, rather than on tumor metastasis itself, to avoid confounding effects of uncertainties derived from various factor...
Source: Artificial Intelligence in Medicine - October 22, 2018 Category: Bioinformatics Source Type: research

Pathological image compression for big data image analysis: Application to hotspot detection in breast cancer
Publication date: Available online 25 September 2018Source: Artificial Intelligence in MedicineAuthor(s): M. Khalid Khan Niazi, Y. Lin, F. Liu, A. Ashok, M.W. Marcellin, G. Tozbikian, M.N. Gurcan, A. BilginAbstractIn this paper, we propose a pathological image compression framework to address the needs of Big Data image analysis in digital pathology. Big Data image analytics require analysis of large databases of high-resolution images using distributed storage and computing resources along with transmission of large amounts of data between the storage and computing nodes that can create a major processing bottleneck. The ...
Source: Artificial Intelligence in Medicine - October 4, 2018 Category: Bioinformatics Source Type: research

A methodology for customizing clinical tests for esophageal cancer based on patient preferences
Publication date: Available online 29 September 2018Source: Artificial Intelligence in MedicineAuthor(s): Asis Roy, Sourangshu Bhattacharya, Kalyan GuinAbstractBackgroundClinical tests for diagnosis of any disease may be expensive, uncomfortable, time consuming and can have side effects e.g. barium swallow test for esophageal cancer. Although we can predict non-existence of esophageal cancer with near 100% certainty just using demographics, lifestyle, medical history information, and a few basic clinical tests but our objective is to devise a general methodology for customizing tests with user preferences to avoid expensiv...
Source: Artificial Intelligence in Medicine - October 4, 2018 Category: Bioinformatics Source Type: research

Predicting hospital associated disability from imbalanced data using supervised learning
Publication date: Available online 3 October 2018Source: Artificial Intelligence in MedicineAuthor(s): Mirka Saarela, Olli-Pekka Ryynänen, Sami ÄyrämöAbstractHospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. This is accomplished by studying the outcome of hospitalization of elderly patie...
Source: Artificial Intelligence in Medicine - October 4, 2018 Category: Bioinformatics Source Type: research

Towards a modular decision support system for radiomics: A case study on rectal cancer
Publication date: Available online 4 October 2018Source: Artificial Intelligence in MedicineAuthor(s): Roberto Gatta, Mauro Vallati, Nicola Dinapoli, Carlotta Masciocchi, Jacopo Lenkowicz, Davide Cusumano, Calogero Casá, Alessandra Farchione, Andrea Damiani, Johan van Soest, Andre Dekker, Vincenzo ValentiniAbstractFollowing the personalized medicine paradigm, there is a growing interest in medical agents capable of predicting the effect of therapies on patients, by exploiting the amount of data that is now available for each patient. In disciplines like oncology, where images and scans are available, the exploitatio...
Source: Artificial Intelligence in Medicine - October 4, 2018 Category: Bioinformatics Source Type: research

Predicting ICU readmission using grouped physiological and medication trends
ConclusionsGrouped physiological and medication trends carry predictive information for ICU readmission risk. In order to build predictive models with higher accuracy, we should add grouped physiological and medication trends as complementary features to snapshot measurements. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 11, 2018 Category: Bioinformatics Source Type: research

A survey on computer-assisted Parkinson's Disease diagnosis
ConclusionsThe main focus of this survey is to consider computer-assisted diagnosis, and how effective they can be when handling the problem of PD identification. Also, the main contribution of this review is to consider very recent works only, mainly from 2015 and 2016. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 8, 2018 Category: Bioinformatics Source Type: research

Association measures for estimating semantic similarity and relatedness between biomedical concepts
Publication date: Available online 7 September 2018Source: Artificial Intelligence in MedicineAuthor(s): Sam Henry, Alex McQuilkin, Bridget T. McInnesAbstractAssociation measures quantify the observed likelihood a term pair co-occurs versus their predicted co-occurrence together if by chance. This is based both on the terms’ individual occurrence frequencies, and their mutual co-occurrence frequencies. One application of association scores is estimating semantic relatedness, which is critical for many natural language processing applications, such as clustering of biomedical and clinical documents and the development...
Source: Artificial Intelligence in Medicine - September 7, 2018 Category: Bioinformatics Source Type: research

An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation
This article presents our steps to integrate complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated faceted search tool, accompanied by the visualisation of results of automatic information extraction from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals. Our exemplary use cases are nephrology and mammography. The software was first developed in the nephrology domain and then adapted to the mammography use case....
Source: Artificial Intelligence in Medicine - September 6, 2018 Category: Bioinformatics Source Type: research

Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis
Publication date: Available online 6 September 2018Source: Artificial Intelligence in MedicineAuthor(s): Massimo W. Rivolta, Md. Aktaruzzaman, Giovanna Rizzo, Claudio L. Lafortuna, Maurizio Ferrarin, Gabriele Bovi, Daniela R. Bonardi, Andrea Caspani, Roberto SassiAbstractGait and balance disorders are among the main predisposing factors of falls in elderly. Clinical scales are widely employed to assess the risk of falling, but they require trained personnel. We investigate the use of objective measures obtained from a wearable accelerometer to evaluate the fall risk, determined by the Tinetti clinical scale. Seventy-nine p...
Source: Artificial Intelligence in Medicine - September 6, 2018 Category: Bioinformatics Source Type: research

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
We present an extensive literature review of CNN techniques applied in brain magnetic resonance imaging (MRI) analysis, focusing on the architectures, pre-processing, data-preparation and post-processing strategies available in these works. The aim of this study is three-fold. Our primary goal is to report how different CNN architectures have evolved, discuss state-of-the-art strategies, condense their results obtained using public datasets and examine their pros and cons. Second, this paper is intended to be a detailed reference of the research activity in deep CNN for brain MRI analysis. Finally, we present a perspective...
Source: Artificial Intelligence in Medicine - September 6, 2018 Category: Bioinformatics Source Type: research

Surgical motion analysis using discriminative interpretable patterns
ConclusionsThe proposed approach is an interesting addition to existing learning tools for surgery as it provides a way to obtain a feedback on which parts of an exercise have been used to classify the attempt as correct or incorrect. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 30, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: August 2018Source: Artificial Intelligence in Medicine, Volume 90Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 24, 2018 Category: Bioinformatics Source Type: research

Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance
In this study, we propose a framework for drug safety signal detection by harnessing online health community data, a timely, informative, and publicly available data source. Concretely, we used MedHelp as the data source to collect patient-contributed content based on which a weighted heterogeneous network was constructed. We extracted topological features from the network, quantified them with different weighting methods, and used supervised learning method for both ADR and DDI signal detection. In addition, after identifying DDI signals, we proposed a new metric, named Interaction Ratio, to identify associated ADRs due t...
Source: Artificial Intelligence in Medicine - August 7, 2018 Category: Bioinformatics Source Type: research

Recent advances in extracting and processing rich semantics from medical texts
Publication date: Available online 3 August 2018Source: Artificial Intelligence in MedicineAuthor(s): Kerstin Denecke, Frank van Harmelen (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 3, 2018 Category: Bioinformatics Source Type: research

Causality assessment of adverse drug reaction reports using an expert-defined Bayesian network
Publication date: Available online 2 August 2018Source: Artificial Intelligence in MedicineAuthor(s): Pedro Pereira Rodrigues, Daniela Ferreira-Santos, Ana Silva, Jorge Polónia, Inês Ribeiro-VazAbstractIn pharmacovigilance, reported cases are considered suspected adverse drug reactions (ADR). Health authorities have thus adopted structured causality assessment methods, allowing the evaluation of the likelihood that a drug was the causal agent of an adverse reaction. The aim of this work was to develop and validate a new causality assessment support system used in a regional pharmacovigilance centre. A Bayesian...
Source: Artificial Intelligence in Medicine - August 2, 2018 Category: Bioinformatics Source Type: research

Dependence between cognitive impairment and metabolic syndrome applied to a Brazilian elderly dataset
In this study, a dataset consisting of a Brazilian elderly sample was modelled using a Bayesian Network (BN) approach to uncover connections between cognitive performance measures and potential influence factors. Regarding its structure (a Directed Acyclic Graph), it was investigated the probabilistic dependence mechanism between two variables of medical interest: the suspected risk factor known as Metabolic Syndrome (MetS) and the indicator of mental decline referred to as Cognitive Impairment (CI). In this investigation, the concept known in the context of a BN as D-separation has been employed. Results of the conducted ...
Source: Artificial Intelligence in Medicine - August 1, 2018 Category: Bioinformatics Source Type: research

Diagnosis labeling with disease-specific characteristics mining
Publication date: Available online 31 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Jun Guo, Xuan Yuan, Xia Zheng, Pengfei Xu, Yun Xiao, Baoying LiuAbstractData analysis and management of huge volumes of medical data have attracted enormous attention, since discovering knowledge from the data can benefit both caregivers and patients. In this paper, we focus on learning disease labels from medical data of patients in Intensive Care Units (ICU). Specifically, we extract features from two main sources, medical charts and notes. We apply the Bag-of-Words (BoW) model to encode the features. Different from most ...
Source: Artificial Intelligence in Medicine - August 1, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: July 2018Source: Artificial Intelligence in Medicine, Volume 89Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 28, 2018 Category: Bioinformatics Source Type: research

Abdominal, multi-organ, auto-contouring method for online adaptive magnetic resonance guided radiotherapy: An intelligent, multi-level fusion approach
ConclusionWith a DSI significantly higher than the usually reported 0.7, our novel algorithm yields a high segmentation accuracy. To our knowledge, this is the first fully automated contouring approach using T1 MRI images for adaptive radiotherapy. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 25, 2018 Category: Bioinformatics Source Type: research

Process models of interrelated speech intentions from online health-related conversations
Publication date: Available online 18 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Elena V. Epure, Dario Compagno, Camille Salinesi, Rébecca Deneckere, Marko Bajec, Slavko Ĺ˝itnikAbstractBeing related to the adoption of new beliefs, attitudes and, ultimately, behaviors, analyzing online communication is of utmost importance for medicine. Multiple health care, academic communities, such as information seeking and dissemination and persuasive technologies, acknowledge this need. However, in order to obtain understanding, a relevant way to model online communication for the study of behavior is requir...
Source: Artificial Intelligence in Medicine - July 18, 2018 Category: Bioinformatics Source Type: research

Detecting mental fatigue from eye-tracking data gathered while watching video: Evaluation in younger and older adults
Publication date: Available online 17 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Yasunori Yamada, Masatomo KobayashiAbstractHealth monitoring technology in everyday situations is expected to improve quality of life and support aging populations. Mental fatigue among health indicators of individuals has become important due to its association with cognitive performance and health outcomes, especially in older adults. Previous models using eye-tracking measures allow inference of fatigue during cognitive tasks, such as driving, but they require us to engage in specific cognitive tasks. In addition, previo...
Source: Artificial Intelligence in Medicine - July 18, 2018 Category: Bioinformatics Source Type: research

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data
Publication date: Available online 14 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Aaron N. Richter, Taghi M. KhoshgoftaarAbstractAdvancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially curative treatments are performed. Predictive models can be built using historical patient data to model the characteristics of patients that developed cancer or relapsed. These models can then be deployed into clinical settings to ...
Source: Artificial Intelligence in Medicine - July 15, 2018 Category: Bioinformatics Source Type: research

Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis
Publication date: Available online 11 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Elham Askari, Seyed Kamaledin Setarehdan, Ali Sheikhani, Mohammad Reza Mohammadi, Mohammad TeshnehlabAbstractThe brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). Th...
Source: Artificial Intelligence in Medicine - July 11, 2018 Category: Bioinformatics Source Type: research

Origins of the Arden Syntax
Publication date: Available online 2 July 2015Source: Artificial Intelligence in MedicineAuthor(s): George Hripcsak, Ove B. Wigertz, Paul D. ClaytonAbstractThe Arden Syntax originated in the 1980's, when several knowledge-based systems began to show promise, but researchers recognized the burden of recreating these systems at every institution. Derived initially from Health Evaluation through Logical Processing (HELP) and the Regenstrief Medical Record System (RMRS), the Arden Syntax defines medical logic that can be encoded as independent rules, such as reminders and alerts, with the hope of creating a public library of r...
Source: Artificial Intelligence in Medicine - July 10, 2018 Category: Bioinformatics Source Type: research