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IEEE Journal of Biomedical and Health Informatics

Ioannis T Pavlidis, Ivan Garza, Panagiotis Tsiamyrtzis, Malcolm Dcosta, Jerry W Swanson, Thomas Krouskop, James Levine
This article documents thermophysiological patterns associated with migraine episodes, where the inner canthi and supraorbital temperatures drop significantly compared to normal conditions. These drops are likely due to vasoconstriction of the ophthalmic arteries under the inner canthi and sympathetic activation of the eccrine glands in the supraorbital region, respectively. The patterns were observed on eight migraine patients and meticulously quantified using advance computational methods, capable of delineating small anatomical structures in thermal imagery and tracking them automatically over time...
July 12, 2018: IEEE Journal of Biomedical and Health Informatics
Konstantin Korotkov, Josep Quintana, Ricard Campos, Miriam America Jesus Silva, Pablo Iglesias, Susana Puig, Josep Malvehy, Rafael Garcia
Total body photography is used for early detection of malignant melanoma, primarily as a means of temporal skin surface monitoring. In prior work, we presented a scanner with a set of algorithms to map and detect changes in pigmented skin lesions, thus demonstrating that it is possible to fully automate the process of total body image acquisition and processing. The key procedure in these algorithms is skin lesion matching which determines whether two images depict the same real lesion. In this paper, we aim to improve it with respect to false positive and negative outcomes...
July 12, 2018: IEEE Journal of Biomedical and Health Informatics
Weixing Liu, Dagong Jia, Jing Chao, Hongxia Zhang, Tiegen Liu, Yimo Zhang, Ye Sun
Human skin temperature mapping provides abundant information of physiological conditions of human body, which provides supplementary or alternative indicators for disease monitoring or diagnosis. The existing models of temperature mapping or temperature field distribution of human skin are generally established by finite element method. Due to the complexity of biological systems, it is challenging to achieve high accuracy mathematical models of temperature field of human skin. The goal of this study is to establish human skin temperature 3D mapping platform by integrating optical fibers and improved GA-BP neural network...
July 10, 2018: IEEE Journal of Biomedical and Health Informatics
Aiying Zhang, Jian Fang, Faming Liang, Vince D Calhoun, Yuping Wang
Schizophrenia (SZ) is a chronic and severe mental disorder that affects how a person thinks, feels, and behaves. It has been proposed that this disorder is related to disrupted brain connectivity. With the development of functional magnetic resonance imaging (fMRI), further exploration of brain connectivity was made possible and this hypothesis has been verified. Region-based networks are commonly used for mapping brain connectivity. However, they fail to illustrate the connectivity within regions of interest (ROIs) and lose precise location information...
July 9, 2018: IEEE Journal of Biomedical and Health Informatics
Dimitris K Iakovidis, George Dimas, Alexandros Karargyris, Federico Bianchi, Gastone Ciuti, Anastasios Koulaouzidis
Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body structures, and their application is rapidly extending to cover the increasing needs for accurate therapeutic interventions. In this context, it is essential for such systems to be able to perform measurements, such as measuring the distance travelled by a wireless capsule endoscope, so as to determine the location of a lesion in the gastrointestinal (GI) tract, or to measure the size of lesions for diagnostic purposes...
July 9, 2018: IEEE Journal of Biomedical and Health Informatics
Wenfeng Song, Shuai Li, Ji Liu, Hong Qin, Bo Zhang, Zhang Shuyang, Aimin Hao
Thyroid ultrasonography is a widely-used clinical technique for nodule diagnosis in thyroid regions. However, it remains difficult to detect and recognize the nodules due to low contrast, high noise, and diverse appearance of nodules. In today's clinical practice, senior doctors could pinpoint nodules by analyzing global context features, local geometry structure, and intensity changes, which would require rich clinical experience accumulated from hundreds and thousands of nodule case studies. To alleviate doctors' tremendous labor in the diagnosis procedure, we advocate a machine learning approach to the detection and recognition tasks in this paper...
July 3, 2018: IEEE Journal of Biomedical and Health Informatics
Bo Hu, Ye Tang, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu
The visual attributes of cells, such as the nuclear morphology and chromatin openness, are critical for histopathology image analysis. By learning cell-level visual representation, we can obtain a rich mix of features that are highly reusable for various tasks, such as cell-level classification, nuclei segmentation, and cell counting. In this paper, we propose a unified generative adversarial networks architecture with a new formulation of loss to perform robust cell-level visual representation learning in an unsupervised setting...
July 3, 2018: IEEE Journal of Biomedical and Health Informatics
Arunava Chakravarty, Jayanthi Sivaswamy
The level set based deformable models (LDM) are commonly used for medical image segmentation. However, they rely on a handcrafted curve evolution velocity that needs to be adapted for each segmentation task. The Convolutional Neural Networks (CNN) address this issue by learning robust features in a supervised end-to-end manner. However, CNNs employ millions of network parameters which require a large amount of training data to prevent over-fitting and also increases its memory requirement and computation time during testing...
July 3, 2018: IEEE Journal of Biomedical and Health Informatics
Cheng Xie, Hongming Cai, Yun Yang, Lihong Jiang, Po Yang
Driven by the automation technologies and health informatics of Industry 4.0, hospitals in China have deployed a complete automation system/platform for healthcare services accessing. Without much more Internet knowledge, elderlies usually seek the third-party to assist them to get healthcare services from Web or APPs, it consequently results in an unexpected situation that scalpers could grab all healthcare services booking by unrighteous means in order to re-sell to elderlies for a much higher price. Moreover, it is hard for physicians to identify the scalpers due to the complexity, ad-hoc and multi-scenario nature of healthcare processes...
July 2, 2018: IEEE Journal of Biomedical and Health Informatics
Pingjian Ding, Rui Yin, Jiawei Luo, Chee Keong Kwoh
Combinatorial therapy may reduce drug side effects and improve drug efficacy, making combination therapy a promising strategy to treat complex diseases. However, in the existing computational methods, the natural properties and network knowledge of drugs have not been adequately and simultaneously considered, making it difficult to identify effective drug combinations. Computational methods that incorporate multiple sources of information (biological, chemical, pharmacological and network knowledge) offer more opportunities to screen synergistic drug combinations...
July 2, 2018: IEEE Journal of Biomedical and Health Informatics
Alba Martin-Yebra, Pablo Laguna, Iwona Cygankiewicz, Antonio Bayes de Luna, Enrico Gianluca Caiani, Juan Pablo Martinez
OBJECTIVE: Atrial fibrillation (AF) rhythm gives rise to an irregular response in ventricular activity, preventing the use of standard ECG-derived risk markers based on ventricular repolarization heterogeneity under this particular condition. In this study we proposed new indices to quantify repolarization variations in AF patients, assessing their stratification performance in a chronic heart failure (CHF) population with AF. METHODS: We developed a method based on a selective bin averaging technique...
June 28, 2018: IEEE Journal of Biomedical and Health Informatics
Mikko Peltokangas, Velipekka Suominen, Damir Vakhitov, Janne Korhonen, Jarmo Verho, Ville M Mattila, Pekka Romsi, Jukka Lekkala, Antti Vehkaoja, Niku Oksala
We analyze the changes in upper and lower limb pulse transit times (PTT) caused by peripheral artery disease (PAD) and its treatment with percutaneous transluminal angioplasty (PTA) of the superficial femoral artery. PTTs were extracted from the photoplethysmograms (PPG) recorded from an index finger and 2nd toes. PTTs were defined between the R-peaks of the ECG and different reference points of the (PPG): foot and peak points, maxima of 1st and 2nd derivative, and by means of intersecting tangents method. Also the PTTs between the toe and finger pulses were analyzed...
June 28, 2018: IEEE Journal of Biomedical and Health Informatics
Wei Li, Bonnie M Liu, Dongxi Liu, Ren Ping Liu, Peishun Wang, Shoushan Luo, Wei Ni
Attribute-based encryption has been a promising encryption technology to secure personal health records (PHRs) sharing in cloud computing. PHRs consist of the patient data often collected from various sources including hospitals and general practice centres. Different patients' access policies have a common access sub-policy. In this paper, we propose a novel attribute-based encryption scheme for fine-grained and flexible access control to PHRs data in cloud computing. The scheme generates shared information by the common access sub-policy which is based on different patients' access policies...
June 25, 2018: IEEE Journal of Biomedical and Health Informatics
Qiaokang Liang, Yang Nan, Gianmarc Coppola, Kunlin Zou, Wei Sun, Dan Zhang, Guanzhen Yu
Recent advances in deep learning have produced encouraging results for biomedical image segmentation; however, outcomes rely heavily on comprehensive annotation. In this paper, we propose a neural network architecture and a new algorithm, known as overlapped region forecast, for the automatic segmentation of gastric cancer images. To the best of our knowledge, this report describes the first time that deep learning has been applied to the segmentation of gastric cancer images. Moreover, a reiterative learning framework that achieves superior performance without pre-training or further manual annotation is presented to train a simple network on weakly annotated biomedical images...
June 25, 2018: IEEE Journal of Biomedical and Health Informatics
Zhao Guo, Xiaohui Xiao, Haoyong Yu
Patient transportation in hospitals faces many challenges, including the limited manpower, work-related injuries, low efficiency of current bed pushing methods. This paper presents a new motorized robotic bed mover with omni-directional mobility to address this problem. This device is composed of an omni-directional mobility unit; a force sensing based human-machine interface (HMI) and control hardware with batteries and electronics. The proposed bed mover can be attached to the bottom of a manual hospital stretcher, transforming it into a powered omni-directional bed (OmniBed) that can be used only by one person...
June 21, 2018: IEEE Journal of Biomedical and Health Informatics
Loreen Pogrzeba, Thomas Neumann, Markus Wacker, Bernhard Jung
Objective assessment in long-term rehabilitation under real-life recording conditions is a challenging task. We propose a data-driven method to evaluate changes in motor function under uncontrolled, long-term conditions with the low-cost Microsoft Kinect Sensor. Instead of using human ratings as ground truth data, we propose kinematic features of hand motion, healthy reference trajectories derived by principal component regression, and methods from machine learning to analyze the progression of motor function...
June 15, 2018: IEEE Journal of Biomedical and Health Informatics
Mengxing Huang, Huirui Han, Lefei Li, Hao Wang, Yu Zhang, Uzair Aslam Bhatti
To keep pace with the developments in medical informatics, health medical data is being collected continually. But, owing to the diversity of its categories and sources, medical data has become highly complicated in many hospitals that it now needs Clinical Decision Support (CDS) system for its management. To effectively utilize the accumulating health data, we propose a CDS framework that can integrate heterogeneous health data from different sources, such as laboratory test results, basic information of patients, and health records into a consolidated representation of features of all patients...
June 12, 2018: IEEE Journal of Biomedical and Health Informatics
Haijun Lei, Yuting Wen, Ahmed Elazab, Ee-Leng Tan, Yujia Zhao, Baiying Lei
Predicting the protein-protein interactions (PPIs) has played an important role in many applications. Hence, a novel computational method for PPIs prediction is highly desirable. PPIs endow with protein amino acid mutation rate and two physicochemical properties of protein (e.g., hydrophobicity, and hydrophilicity). Deep polynomial network (DPN) is well-suited to integrate these modalities since it can represent any function on a finite sample dataset via the supervised deep learning algorithm. We propose a multimodal DPN (MDPN) algorithm to effectively integrate these modalities to enhance prediction performance...
June 12, 2018: IEEE Journal of Biomedical and Health Informatics
Ana Catarina Fidalgo Barata, Emre M Celebi, Jorge Marques
Dermoscopy image analysis (DIA) is a growing field, with works being published every week. This makes it difficult not only to keep track of all the contributions, but also for new researchers to identify relevant information and new directions to be explored. Several surveys have been written in the past decade, but these tend to cover all of the steps of a CAD system, which can be overwhelming. Moreover, in these works, each of the steps is briefly discussed due to lack of space. Among the different blocks of the CAD system, the most relevant is the one devoted to feature extraction...
June 11, 2018: IEEE Journal of Biomedical and Health Informatics
Xiujuan Zheng, Wentao Wei, Qiu Huang, Shaoli Song, Gang Huang
The glomerular filtration rate (GFR) is a crucial index to measure renal function. In daily clinical practice, the GFR can be estimated using the Gates method, which requires the clinicians to define the region of interest (ROI) for the kidney and the corresponding background in dynamic renal scintigraphy. The manual placement of ROIs to estimate the GFR is subjective and labor-intensive, however, making it an undesirable and unreliable process. This work presents a fully automated ROI detection method to achieve accurate and robust GFR estimations...
June 11, 2018: IEEE Journal of Biomedical and Health Informatics
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