Editorial Board
Publication date: June 2019Source: Artificial Intelligence in Medicine, Volume 97Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 14, 2019 Category: Bioinformatics Source Type: research

A Deep Survival Analysis Method Based on Ranking
Publication date: Available online 6 June 2019Source: Artificial Intelligence in MedicineAuthor(s): Bingzhong Jing, Tao Zhang, Zixian Wang, Ying Jin, Kuiyuan Liu, Wenze Qiu, Liangru Ke, Ying Sun, Caisheng He, Dan Hou, Linquan Tang, Xing Lv, Chaofeng LiAbstractSurvival analyses of populations and the establishment of prognoses for individual patients are important activities in the practice of medicine. Standard survival models, such as the Cox proportional hazards model, require extensive feature engineering or prior knowledge to model at an individual level. Some survival analysis models can avoid these problems by using ...
Source: Artificial Intelligence in Medicine - June 8, 2019 Category: Bioinformatics Source Type: research

Distant Supervision for Treatment Relation Extraction by Leveraging MeSH Subheadings
In this study, we propose a novel distant supervision approach for relation extraction of binary treatment relationships such that high quality positive/negative training examples are generated from PubMed abstracts by leveraging associated MeSH subheadings. The quality of generated examples is assessed based on the quality of supervised models they induce; that is, the mean performance of trained models (derived via bootstrapped ensembling) on a gold standard test set is used as a proxy for data quality. We show that our approach is preferable to traditional distant supervision for treatment relations and is closer to hum...
Source: Artificial Intelligence in Medicine - June 8, 2019 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: May 2019Source: Artificial Intelligence in Medicine, Volume 96Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 3, 2019 Category: Bioinformatics Source Type: research

Supporting the Distributed Execution of Clinical Guidelines by Multiple Agents
Publication date: Available online 18 May 2019Source: Artificial Intelligence in MedicineAuthor(s): Alessio Bottrighi, Luca Piovesan, Paolo TerenzianiAbstractClinical guidelines (GLs) are widely adopted in order to improve the quality of patient care, and to optimize it. To achieve such goals, their application on a specific patient usually requires the interventions of different agents, with different roles (e.g., physician, nurse), abilities (e.g., specialist in the treatment of alcohol-related problems) and contexts (e.g., many chronic patients may be treated at home). Additionally, the responsibility of the application...
Source: Artificial Intelligence in Medicine - May 19, 2019 Category: Bioinformatics Source Type: research

Texture descriptors and voxels for the early diagnosis of Alzheimer’s disease
ConclusionsEnsembles of texture descriptors combine partially uncorrelated information with respect to standard approaches based on voxels, feature selection, and classification by SVM. In other words, the fusion of a system based on voxels and an ensemble of texture descriptors enhances the performance of voxel-based approaches. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 18, 2019 Category: Bioinformatics Source Type: research

Combining Clustering and Classification Ensembles: A Novel Pipeline to Identify Breast Cancer Profiles
Publication date: Available online 15 May 2019Source: Artificial Intelligence in MedicineAuthor(s): Utkarsh Agrawal, Daniele Soria, Christian Wagner, Jonathan Garibaldi, Ian O. Ellis, John M.S. Bartlett, David Cameron, Emad A. Rakha, Andrew R. GreenAbstractBreast Cancer is one of the most common causes of cancer death in women, representing a very complex disease with varied molecular alterations. To assist breast cancer prognosis, the classification of patients into biological groups is of great significance for treatment strategies. Recent studies have used an ensemble of multiple clustering algorithms to elucidate the m...
Source: Artificial Intelligence in Medicine - May 16, 2019 Category: Bioinformatics Source Type: research

Recurrent neural networks with Segment Attention and Entity Description for relation extraction from clinical texts
Publication date: Available online 2 May 2019Source: Artificial Intelligence in MedicineAuthor(s): Zhi Li, Jinshan Yang, Xu Gou, Xiaorong QiAbstractAt present, great progress has been achieved on the relation extraction for clinical texts, but we have noticed that the current models have great drawbacks when dealing with long sentences and multiple entities in a sentence. In this paper, we propose a novel neural network architecture based on Bidirectional Long Short-Term Memory Networks for relation classification. Firstly, we utilize a concat-attention mechanism for capturing the most important context words for relation ...
Source: Artificial Intelligence in Medicine - May 4, 2019 Category: Bioinformatics Source Type: research

Sparse Support Vector Machines with L0 Approximation for Ultra-high Dimensional Omics Data
Publication date: Available online 30 April 2019Source: Artificial Intelligence in MedicineAuthor(s): Zhenqiu Liu, David Elashoff, Steven PiantadosiAbstractOmics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L2 norm for the primal variables, only lead to sparse solutions for the dual variables. L1 based SVMs, directly minimizing the L1 norm, have been used for feature selection with omics data. However, most current methods directly solve the primal formulations of the problem, which are not computationally scalable. The computational compl...
Source: Artificial Intelligence in Medicine - May 1, 2019 Category: Bioinformatics Source Type: research

Incorporated region detection and classification using deep convolutional networks for bone age assessment
Publication date: Available online 30 April 2019Source: Artificial Intelligence in MedicineAuthor(s): Toan Duc Bui, Jae-Joon Lee, Jitae ShinAbstractBone age assessment plays an important role in the endocrinology and genetic investigation of patients. In this paper, we proposed a deep learning-based approach for bone age assessment by integration of the Tanner-Whitehouse (TW3) methods and deep convolution networks based on extracted regions of interest (ROI)-detection and classification using Faster-RCNN and Inception-v4 networks, respectively. The proposed method allows exploration of expert knowledge from TW3 and feature...
Source: Artificial Intelligence in Medicine - May 1, 2019 Category: Bioinformatics Source Type: research

Neural Transfer Learning for Assigning Diagnosis Codes to EMRs
ConclusionWe show that transfer learning can improve CNN performance for EMR coding in the presence of data sparsity issues. Furthermore, we find that our proposed transfer learning approach outperforms other methods with respect to macro F-score. Finally, we analyze how transfer learning impacts codes with respect to code frequency. We find that we achieve greater improvement on infrequent codes compared to improvements in most frequent codes. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 12, 2019 Category: Bioinformatics Source Type: research

Detection of protein complexes from multiple protein interaction networks using graph embedding
Publication date: Available online 9 April 2019Source: Artificial Intelligence in MedicineAuthor(s): Xiaoxia Liu, Zhihao Yang, Shengtian Sang, Hongfei Lin, Jian Wang, Bo XuAbstractCellular processes are typically carried out by protein complexes rather than individual proteins. Identifying protein complexes is one of the keys to understanding principles of cellular organization and function. Also, protein complexes are a group of interacting genes underlying similar diseases, which points out the therapeutic importance of protein complexes. With the development of life science and computing science, an increasing amount of...
Source: Artificial Intelligence in Medicine - April 10, 2019 Category: Bioinformatics Source Type: research

A Data-driven Approach to Referable Diabetic Retinopathy Detection
Conclusion: Additional boost strategies can improve performance substantially, but it is important to evaluate whether the additional (computation- and implementation-) complexity of each improvement is worth its benefits. We also corroborate that novel families of data-driven methods are the state of the art for diabetic retinopathy screening. Significance: By learning powerful discriminative patterns directly from available training retinal images, it is possible to perform referral diagnostics without detecting individual lesions. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 28, 2019 Category: Bioinformatics Source Type: research

Feature-weighted Survival Learning Machine for COPD Failure Prediction
Publication date: Available online 28 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Jianfei Zhang, Shengrui Wang, Josiane Courteau, Lifei Chen, Gongde Guo, Alain VanasseAbstractChronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting such failure is crucial to early intervention and decision-making, making this a very important research issue. Current analysis methods address all risk factors in medical records indisc...
Source: Artificial Intelligence in Medicine - March 28, 2019 Category: Bioinformatics Source Type: research

Prediction of fetal state from the cardiotocogram recordings using neural network models
In this study, many diverse approaches are suggested for predicting fetal state classes based on artificial intelligence. The various topologies of multi-layer architecture of a sub-adaptive neuro fuzzy inference system (MLA-ANFIS) using multiple input features, neural networks (NN), deep stacked sparse auto-encoders (DSSAEs), and deep-ANFIS models are implemented on a CTG data set. Experimental results contributing to DSSAE are more accurate than other suggested techniques to predict fetal state. The proposed method achieved a sensitivity of 99.716, specificity of 97.500 and geometric mean of 98.602 with accuracy of 99.50...
Source: Artificial Intelligence in Medicine - March 21, 2019 Category: Bioinformatics Source Type: research

OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools.
Publication date: Available online 19 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Olivier Palombi, Fabrice Jouanot, Nafissetou Nziengam, Behrooz Omidvar-Tehrani, Marie-Christine Rousset, Adam SanchezAbstractWe introduce OntoSIDES, the core of an ontology-based learning management system in Medicine, in which the educational content, the traces of students’ activities and the correction of exams are linked and related to items of an official reference program in a unified RDF data model. OntoSIDES is an RDF knowledge base comprised of a lightweight domain ontology that serves as a pivot high-level ...
Source: Artificial Intelligence in Medicine - March 21, 2019 Category: Bioinformatics Source Type: research

Complexity Perception Classification Method for Tongue Constitution Recognition
Publication date: Available online 20 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Jiajiong Ma, Guihua Wen, Changjun Wang, Lijun JiangAbstractThe body constitution is much related to the diseases and the corresponding treatment programs in Traditional Chinese Medicine. It can be recognized by the tongue image diagnosis, so that it is essentially regarded as a problem of tongue image classification, where each tongue image is classified into one of nine constitution types. This paper first presents a system framework to automatically identify the constitution through natural tongue images, where deep conv...
Source: Artificial Intelligence in Medicine - March 21, 2019 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: April 2019Source: Artificial Intelligence in Medicine, Volume 95Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 21, 2019 Category: Bioinformatics Source Type: research

Dynamic thresholding networks for schizophrenia diagnosis
This study aims to develop an effective dynamic thresholding brain networks method to diagnose schizophrenia.MethodsIn this study, we proposed a time-varying window length DFC method based on dynamic time warping to construct brain functional networks. To further eliminate the influence of spurious connections caused by noise, orthogonal minimum spanning tree was applied in these networks to generate time-varying window length dynamic thresholding FC (TVWDTFC) networks. To validate the effectiveness of our proposed method, experiments were conducted on a dataset, which including 56 individuals with schizophrenia and 74 hea...
Source: Artificial Intelligence in Medicine - March 19, 2019 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: March 2019Source: Artificial Intelligence in Medicine, Volume 94Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 12, 2019 Category: Bioinformatics Source Type: research

Mining Heterogeneous Network for Drug Repositioning using Phenotypic Information Extracted from Social Media and Pharmaceutical Databases
Publication date: Available online 9 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Christopher C. Yang, Mengnan ZhaoAbstractDrug repositioning has drawn significant attention for drug development in pharmaceutical research and industry, because of its advantages in cost and time compared with the de novo drug development. The availability of biomedical databases and online health-related information, as well as the high-performance computing, empowers the development of computational drug repositioning methods. In this work, we developed a systematic approach that identifies repositioning drugs based on h...
Source: Artificial Intelligence in Medicine - March 10, 2019 Category: Bioinformatics Source Type: research

Estimation of Echocardiogram parameters with the aid of Impedance Cardiography and Artificial Neural Networks
Publication date: Available online 8 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Sudipta Ghosh, Bhabani Prasad Chattopadhyay, Ram Mohan Roy, Jayanta Mukherjee, Manjunatha MahadevappaAbstractThe advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming. It is expected to spread as an epidemic by 2030. Present methods of determining the health of one's heart include doppler based echocardiogram, MDCT (Multi Detector Computed Tomography), among various other invasive and non-invasive hemodynamic monitoring techniques. These methods require expert supervision and costly...
Source: Artificial Intelligence in Medicine - March 10, 2019 Category: Bioinformatics Source Type: research

Reliability-based Robust Multi-atlas Label Fusion for Brain MRI Segmentation
Publication date: Available online 8 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Liang Sun, Chen Zu, Wei Shao, Junye Guang, Daoqiang Zhang, Mingxia LiuAbstractLabel fusion is one of the key steps in multi-atlas based segmentation of structural magnetic resonance (MR) images. Although a number of label fusion methods have been developed in literature, most of those existing methods fail to address two important problems, i.e., 1) compared with boundary voxels, inner voxels usually have higher probability (or reliability) to be correctly segmented, and 2) voxels with high segmentation reliability (after i...
Source: Artificial Intelligence in Medicine - March 8, 2019 Category: Bioinformatics Source Type: research

Retinal Blood Vessel Extraction Employing Effective Image Features and Combination of Supervised and Unsupervised Machine Learning Methods
Publication date: Available online 2 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Mahdi Hashemzadeh, Baharak Adlpour AzarAbstractIn medicine, retinal vessel analysis of fundus images is a prominent task for the screening and diagnosis of various ophthalmological and cardiovascular diseases. In this research, a method is proposed for extracting the retinal blood vessels employing a set of effective image features and combination of supervised and unsupervised machine learning techniques. Further to the common features used in extracting blood vessels, three strong features having a significant influence o...
Source: Artificial Intelligence in Medicine - March 5, 2019 Category: Bioinformatics Source Type: research

Fast Density-peaks Clustering for Registration-free Pediatric White Matter Tract Analysis
Publication date: Available online 2 March 2019Source: Artificial Intelligence in MedicineAuthor(s): Xin Fan, Yuzhuo Duan, Shichao Cheng, Yuxi Zhang, Hua ChengAbstractClustering white matter (WM) tracts from diffusion tensor imaging (DTI) is primarily important for quantitative analysis on pediatric brain development. A recently developed algorithm, density peaks (DP) clustering, demonstrates great robustness to the complex structural variations of WM tracts without any prior templates. Nevertheless, the calculation of densities, the core step of DP, is time consuming especially when the number of WM fibers is huge. In thi...
Source: Artificial Intelligence in Medicine - March 5, 2019 Category: Bioinformatics Source Type: research

Autonomous Agents and Multi-Agent Systems Applied in Healthcare
Publication date: Available online 27 February 2019Source: Artificial Intelligence in MedicineAuthor(s): Sara Montagna, Daniel Castro Silva, Pedro Henriques Abreu, Marcia Ito, Michael Ignaz Schumacher, Eloisa Vargiu (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 28, 2019 Category: Bioinformatics Source Type: research

Machine Learning Models Based on the Dimensionality Reduction of Standard Automated Perimetry Data for Glaucoma Diagnosis
ConclusionA glaucoma diagnosis model giving an AUC of 0.912 was constructed by applying machine learning techniques to SAP data. The results show that dimensionality reduction not only reduces dimensions of the input space but also enhances the classification performance. The variable selection results show that the proposed composite variables from visual field clustering play a key role in the diagnosis model. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 26, 2019 Category: Bioinformatics Source Type: research

Using Classification Techniques for Statistical Analysis of Anemia
This study develops a decision support system using data mining techniques that are applied to a database containing data about nutritional factors for children. The data set was taken from NFHS-4, a survey conducted by the Government of India in 2015-16. The work attempts to predict anemia among children and establish a relation between mother’s health and diet during pregnancy and its effects on anemic status of her child. It aims to help parents and clinicians to understand the influence of an infant’s feeding practices and diet on his/her health and provide guidelines regarding diet to prevent anemia. Earli...
Source: Artificial Intelligence in Medicine - February 20, 2019 Category: Bioinformatics Source Type: research

Execution-Time Integration of Clinical Practice Guidelines To Provide Decision Support for Comorbid Conditions
Publication date: Available online 20 February 2019Source: Artificial Intelligence in MedicineAuthor(s): Borna Jafarpour, Samina Raza Abidi, William Van Woensel, Syed Sibte Raza AbidiAbstractPatients with multiple medical conditions (comorbidity) pose major challenges to clinical decision support systems, since the different Clinical Practice Guidelines (CPG) often involve adverse interactions, such as drug-drug or drug-disease interactions. Moreover, opportunities often exist for optimizing care and resources across multiple CPG. These challenges have been taken up in the state of the art, with many approaches focusing on...
Source: Artificial Intelligence in Medicine - February 20, 2019 Category: Bioinformatics Source Type: research

Joint segmentation and classification of retinal arteries/veins from fundus images
ConclusionThe results show that our method outperforms the leading previous works on a public dataset for A/V classification and is by far the fastest.SignificanceThe proposed global AVR calculated on the whole fundus image using our automatic A/V segmentation method can better track vessel changes associated to diabetic retinopathy than the standard local AVR calculated only around the optic disc. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 19, 2019 Category: Bioinformatics Source Type: research

Real-Time Multi-Agent Systems for Telerehabilitation Scenarios
Publication date: Available online 14 February 2019Source: Artificial Intelligence in MedicineAuthor(s): Davide Calvaresi, Mauro Marinoni, Aldo Franco Dragoni, Roger Hilfiker, Michael SchumacherAbstractTelerehabilitation in older adults is most needed in the patient environments, rather than in formal ambulatories or hospitals. Supporting such practices brings significant advantages to patients, their family, formal and informal caregivers, clinicians, and researchers.This paper presents a focus group with experts in physiotherapy and telerehabilitation, debating on the requirements, current techniques and technologies dev...
Source: Artificial Intelligence in Medicine - February 15, 2019 Category: Bioinformatics Source Type: research

Detection of Abnormal Behaviour for Dementia Sufferers using Convolutional Neural Networks
Publication date: Available online 10 February 2019Source: Artificial Intelligence in MedicineAuthor(s): Damla Arifoglu, Abdelhamid BouchachiaAbstractIn recent years, there is a rapid increase in the population of elderly people. However, elderly people may suffer from the consequences of cognitive decline, which is a mental health disorder that primarily affects cognitive abilities such as learning, memory, etc. As a result, the elderly people may get dependent on caregivers to complete daily life tasks. Detecting the early indicators of dementia before it gets worsen and warning the caregivers and medical doctors would b...
Source: Artificial Intelligence in Medicine - February 11, 2019 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: January 2019Source: Artificial Intelligence in Medicine, Volume 93Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 2, 2019 Category: Bioinformatics Source Type: research

MRI denoising by NeighShrink based on chi-square unbiased risk estimation
Publication date: Available online 1 February 2019Source: Artificial Intelligence in MedicineAuthor(s): Chang-Jiang Zhang, Xue-You Huang, Ming-Chao FangAbstractNeighShrink is an efficient image denoising algorithm for the reduction of additive white Gaussian noise. However, it does not perform well in terms of Rician noise removal for MRI (Magnetic Resonance Imaging). Allowing for the characteristics of squared-magnitude MR (Magnetic Resonance) images, which follow a non-central chi-square distribution, the CURE (Chi-Square Unbiased Risk Estimation) is used to determine an optimal threshold for NeighShrink. Therefore, we p...
Source: Artificial Intelligence in Medicine - February 1, 2019 Category: Bioinformatics Source Type: research

A Survey Of Neural Network-based Cancer Prediction Models From Microarray Data
Publication date: Available online 30 January 2019Source: Artificial Intelligence in MedicineAuthor(s): Maisa Daoud, Michael MayoAbstractNeural networks are powerful tools used widely for building cancer prediction models from microarray data. We review the most recently proposed models to highlight the roles of neural networks in predicting cancer from gene expression data. We identified articles published between 2013-2018 in scientific databases using keywords such as cancer classification, cancer analysis, cancer prediction, cancer clustering and microarray data. Analyzing the studies reveals that neural network method...
Source: Artificial Intelligence in Medicine - January 30, 2019 Category: Bioinformatics Source Type: research

Predicting Lab Values for Gastrointestinal Bleeding Patients in the Intensive Care Unit: A Comparative Study on the Impact of Comorbidities and Medications
Publication date: Available online 23 January 2019Source: Artificial Intelligence in MedicineAuthor(s): Golnar K. Mahani, Mohammad-Reza PajoohanAbstractSince a significant number of frequent laboratory blood tests are unnecessary and these tests may have complications, developing a system that could identify unnecessary tests is essential. In this paper, a value prediction approach is presented to predict the values of Calcium and Hematocrit laboratory blood tests for upper gastrointestinal bleeding patients and patients with unspecified hemorrhage in their gastrointestinal tract. The data have been extracted from the MIMI...
Source: Artificial Intelligence in Medicine - January 24, 2019 Category: Bioinformatics Source Type: research

A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity
ConclusionThe results confirm conventional wisdom that discrete-time Bayesian networks are appropriate when learning from regularly spaced clinical time series. Similarly, we found that time series where the missingness occurs completely at random, dynamic Bayesian networks are an appropriate choice. However, for complex clinical time-series data that motivated this research, the continuous-time models are at least competitive and sometimes better than their discrete-time counterparts. Furthermore, continuous-time models provide additional benefits of being able to provide more fine-grained predictions than discrete-time m...
Source: Artificial Intelligence in Medicine - January 23, 2019 Category: Bioinformatics Source Type: research

Explainable artificial intelligence for breast cancer: a visual case-based reasoning approach
Publication date: Available online 14 January 2019Source: Artificial Intelligence in MedicineAuthor(s): Jean-Baptiste Lamy, Boomadevi Sekar, Gilles Guezennec, Jacques Bouaud, Brigitte SéroussiAbstractCase-Based Reasoning (CBR) is a form of analogical reasoning in which the solution for a (new) query case is determined using a database of previous known cases with their solutions. Cases similar to the query are retrieved from the database, and then their solutions are adapted to the query. In medicine, a case usually corresponds to a patient and the problem consists of classifying the patient in a class of diagnostic...
Source: Artificial Intelligence in Medicine - January 15, 2019 Category: Bioinformatics Source Type: research

Normal and Pathological Gait Classification LSTM model
Publication date: Available online 11 January 2019Source: Artificial Intelligence in MedicineAuthor(s): Margarita Khokhlova, Cyrille Migniot, Alexey Morozov, Olga Sushkova, Albert DipandaAbstractComputer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we...
Source: Artificial Intelligence in Medicine - January 11, 2019 Category: Bioinformatics Source Type: research

Active Contour Algorithm with Discriminant Analysis for Delineating Tumors in Positron Emission Tomography
Publication date: Available online 8 January 2019Source: Artificial Intelligence in MedicineAuthor(s): Albert Comelli, Alessandro Stefano, Samuel Bignardi, Giorgio Russo, Maria Gabriella Sabini, Massimo Ippolito, Stefano Barone, Anthony YezziAbstractIn the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one...
Source: Artificial Intelligence in Medicine - January 8, 2019 Category: Bioinformatics Source Type: research

Antigenic: An improved prediction model of protective antigens
Publication date: Available online 3 January 2019Source: Artificial Intelligence in MedicineAuthor(s): M. Saifur Rahman, Md. Khaledur Rahman, Sanjay Saha, M. Kaykobad, M. Sohel RahmanAbstractAn antigen is a protein capable of triggering an effective immune system response. Protective antigens are the ones that can invoke specific and enhanced adaptive immune response to subsequent exposure to the specific pathogen or related organisms. Such proteins are therefore of immense importance in vaccine preparation and drug design. However, the laboratory experiments to isolate and identify antigens from a microbial pathogen are e...
Source: Artificial Intelligence in Medicine - January 4, 2019 Category: Bioinformatics Source Type: research

Denoising of low-dose CT images via low-rank tensor modeling and total variation regularization
Publication date: Available online 31 December 2018Source: Artificial Intelligence in MedicineAuthor(s): Sameera V. Mohd Sagheer, Sudhish N. GeorgeAbstractLow-dose Computed Tomography (CT) imaging is a most commonly used medical imaging modality. Though the reduction in dosage reduces the risk due to radiation, it leads to an increase in noise level. Hence, it is a mandatory requirement to include a noise reduction technique as a pre-and/or post-processing step for better disease diagnosis. The nuclear norm minimization has attracted a great deal of research interest in contemporary years. This paper proposes a low-rank ap...
Source: Artificial Intelligence in Medicine - December 31, 2018 Category: Bioinformatics Source Type: research

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