Computers in Biology and Medicine
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#1Oldrich Kodym (Brno University of Technology)H-Index: 5
#2Michal Španěl (Brno University of Technology)H-Index: 5
Last. Adam Herout (Brno University of Technology)H-Index: 21
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Abstract null null Correct virtual reconstruction of a defective skull is a prerequisite for successful cranioplasty and its automatization has the potential for accelerating and standardizing the clinical workflow. This work provides a deep learning-based method for the reconstruction of a skull shape and cranial implant design on clinical data of patients indicated for cranioplasty. The method is based on a cascade of multi-branch volumetric CNNs that enables simultaneous training on two diffe...
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#1Abdullah Ammar Karcioglu (Ege University)H-Index: 1
#2Hasan Bulut (Ege University)H-Index: 35
Abstract null null The string matching algorithms are among the essential fields in computer science, such as text search, intrusion detection systems, fraud detection, sequence search in bioinformatics. The exact string matching algorithms are divided into two parts: single and multiple. Multiple string matching algorithms involve finding elements of the pattern set P in a given input text T. String matching processes should be done in a time-efficient manner for DNA sequences. As the volume of...
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#1Mohammad Sajad Manuchehri (UT: University of Tehran)H-Index: 1
#2Seyed Kamaledin Setarehdan (UT: University of Tehran)H-Index: 16
Abstract null null Modern medicine cannot ignore the significance of elastography in diagnosis and treatment plans. Despite improvements in accuracy and spatial resolution of elastograms, robustness against noise remains a neglected attribute. A method that can perform in a satisfactory manner under noisy conditions may prove useful for various elastography methods. Here, we propose a method based on eigenvalue decomposition (EVD). In this method, the estimated time delay is defined as the index...
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#1Md. Mustafizur Rahman (Jessore University of Science & Technology)H-Index: 1
#2Ajay Krishno Sarkar (RUET: Rajshahi University of Engineering & Technology)H-Index: 7
Last. Mohammad Ali Moni (UQ: University of Queensland)H-Index: 1
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Abstract null null Assessment of the cognitive functions and state of clinical subjects is an important aspect of e-health care delivery, and in the development of novel human-machine interfaces. A subject can display a range of emotions that significantly influence cognition, and emotion classification through the analysis of physiological signals is a key means of detecting emotion. Electroencephalography (EEG) signals have become a common focus of such development compared to other physiologi...
1 CitationsSource
#1Shane Loeffler (UNCG: University of North Carolina at Greensboro)H-Index: 1
#2Joseph M. Starobin (UNCG: University of North Carolina at Greensboro)H-Index: 10
Abstract null null Every year, nine million people die globally from ischemic heart disease (IHD). There are many methods of early detection of IHD which can help prevent death, but few are able to determine the configuration and severity of this disease. Our study aims to determine the severity and configuration of ischemic zones by implementing the reaction-diffusion analysis of cardiac excitation in a model of the left ventricle of the human heart. Initially, this model is applied to compute ...
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#1M. Aslam (AWKUM: Abdul Wali Khan University Mardan)H-Index: 2
#2Muhammad Shehroz (Virtual University of Pakistan)H-Index: 4
Last. Sahib Gul Afridi (AWKUM: Abdul Wali Khan University Mardan)H-Index: 7
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Abstract null null Chlamydia trachomatis is involved in most sexually transmitted diseases. The species has emerged as a major public health threat due to its multidrug-resistant capabilities, and new therapeutic target inferences have become indispensable to combat its pathogenesis. However, no commercial vaccine is yet available to treat the C. trachomatis infection. In this study, we used the publicly available complete genome sequences of C. trachomatis and performed comparative proteomics a...
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#1Jinshan Xu (Zhejiang University of Technology)H-Index: 7
#1Jinshan Xu (Zhejiang University of Technology)
Last. Alain Pumir (École normale supérieure de Lyon)H-Index: 33
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Abstract null null Preterm labor is the leading cause of neonatal morbidity and mortality in newborns and has attracted significant research attention from many scientific areas. The relationship between uterine contraction and the underlying electrical activities makes uterine electrohysterogram (EHG) a promising direction for detecting and predicting preterm births. However, due to the scarcity of EHG signals, especially those leading to preterm births, synthetic algorithms have been used to g...
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#1Alejandro Edera (CONICET: National Scientific and Technical Research Council)H-Index: 1
#2Ian Small (UWA: University of Western Australia)H-Index: 77
Last. M. Virginia Sanchez-Puerta (National University of Cuyo)H-Index: 13
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Abstract null null In land plant mitochondria, C-to-U RNA editing converts cytidines into uridines at highly specific RNA positions called editing sites. This editing step is essential for the correct functioning of mitochondrial proteins. When using sequence homology information, edited positions can be computationally predicted with high precision. However, predictions based on the sequence contexts of such edited positions often result in lower precision, which is limiting further advances on...
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#1Syed Muhammad Usman (BU: Bahria University)H-Index: 4
#2Shehzad Khalid (BU: Bahria University)H-Index: 20
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Abstract null null In epilepsy, patients suffer from seizures which cannot be controlled with medicines or surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is extremely important so that they can be controlled with medication before they actually occur. Researchers have proposed multiple machine/deep learning based methods to predict epileptic seizures; however, accurate prediction of epileptic seizures with low false positive rate is still a challenge. In this...
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#1Sami Alkadri (McGill University)
#2Nicole Ledwos (Montreal Neurological Institute and Hospital)H-Index: 5
Last. Rolando F. Del Maestro (Montreal Neurological Institute and Hospital)H-Index: 45
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Abstract null null Background null Virtual reality surgical simulators are a safe and efficient technology for the assessment and training of surgical skills. Simulators allow trainees to improve specific surgical techniques in risk-free environments. Recently, machine learning has been coupled to simulators to classify performance. However, most studies fail to extract meaningful observations behind the classifications and the impact of specific surgical metrics on the performance. One benefit ...
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