Papers 816
1 page of 82 pages (816 results)
#1Suraj K. Nayak (NITR: National Institute of Technology Rourkela)H-Index: 9
#2Kishore K. Tarafdar (NITR: National Institute of Technology Rourkela)H-Index: 1
Last. Kunal Pal (NITR: National Institute of Technology Rourkela)H-Index: 36
view all 6 authors...
Abstract Objective In the last few decades, the consumption of cannabis-based products for recreational purposes has dramatically increased. Unfortunately, cannabis consumption has been associated with the incidences of cardiovascular diseases. Hence, there is a necessity for understanding the plausible mechanics of cardiophysiological changes due to cannabis consumption. Accordingly, the current study was designed to understand the suitability of the recurrence quantification analysis (RQA) met...
#1Z. Wu (HDU: Hangzhou Dianzi University)H-Index: 1
#2Xiao Dong Chen (HDU: Hangzhou Dianzi University)H-Index: 73
Last. J. Shen (ZJU: Zhejiang University)H-Index: 1
view all 7 authors...
Abstract null null Background and objective null Based on magnetic resonance imaging (MRI), macroscopic structural and functional connectivity of human brain has been widely explored in the last decade. However, little work has been done on effective connectivity between individual brain parcels. In this preliminary study, we aim to investigate whole-brain effective connectivity networks from resting-state functional MRI (rs-fMRI) images. null null null Material and methods null After the functi...
#1R. Karthik (VIT: Vellore Institute of Technology University)H-Index: 7
#2R. Menaka (VIT: Vellore Institute of Technology University)H-Index: 9
Last. M Nagharjun (VIT: Vellore Institute of Technology University)H-Index: 1
view all 5 authors...
Abstract null null Objective null Breast cancer and breast tumors have been considered to be the most pervasive form of cancer in medical practice. Breast tumors are life-threatening to women, and their early detection could save lives with the proper treatment. Physical methods for detection of Breast Cancer are time-consuming and often prone to a misdiagnosis at classifying tumors. Recent trends in radiological imaging have significantly improved the efficiency and veracity of breast tumor cla...
#1Maheshkumar H. Kolekar (IITP: Indian Institute of Technology Patna)H-Index: 18
#2Chandan Kumar Jha (Indian Institutes of Information Technology)H-Index: 7
Last. P. Kumar (IITP: Indian Institute of Technology Patna)
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Abstract null null Objective null In cardiac patient-care, compression of long-term ECG data is essential to minimize the data storage requirement and transmission cost. Hence, this paper presents a novel electrocardiogram data compression technique which utilizes modified run-length encoding of wavelet coefficients. null null null Method null First, wavelet transform is applied to the ECG data which decomposes it and packs maximum energy to less number of transform coefficients. The wavelet tra...
#1Criseida Ruiz-Aguilar (UNAM: National Autonomous University of Mexico)H-Index: 3
#2U. Olivares-Pinto (UNAM: National Autonomous University of Mexico)H-Index: 3
Last. Ismeli Alfonso (UNAM: National Autonomous University of Mexico)H-Index: 10
view all 5 authors...
Abstract null null Scaffolds for bone tissue applications have been an outstanding alternative to repair and regenerate bone tissue defects caused by traumas or illness. There are many methods available to fabricate porous scaffold such as solvent casting, gas bubble, phase separation, electrospinning, particle-leaching, among others. The particle-leaching technique has shown advantages in bone tissue regeneration applications, the main benefit of this technique is related to the porogen particl...
#1Shenghua He (WUSTL: Washington University in St. Louis)H-Index: 7
#2Jian Wu (WUSTL: Washington University in St. Louis)H-Index: 73
Last. Hua Li (UIUC: University of Illinois Urbana-Champaign)H-Index: 27
view all 8 authors...
Abstract null null Active learning is an effective solution to interactively select a limited number of informative examples and use them to train a learning algorithm that can achieve its optimal performance for specific tasks. It is suitable for medical image applications in which unlabeled data are abundant but manual annotation could be very time-consuming and expensive. However, designing an effective active learning strategy for informative example selection is a challenging task, due to t...
#1M. Latha (Madras Institute of Technology)
#1Manohar Latha (Madras Institute of Technology)H-Index: 2
Last. Ganesan Kavitha (Madras Institute of Technology)H-Index: 8
view all 2 authors...
Abstract Objectives Schizophrenia (SZ) is the most chronic disabling psychotic brain disorder. It is characterized by delusions and auditory hallucinations, as well as impairments in memory. Schizoaffective (SA) signs are co-morbid with SZ and are characterized by symptoms of SZ and mood disorder. Various researches suggest that SZ and SA share a number of equally severe cognitive deficits, but the pathophysiology has not yet been addressed in a comprehensive way. In this work, the heterogeneity...
#1Liaqat Ali (UESTC: University of Electronic Science and Technology of China)H-Index: 13
#2Syed Ahmad Chan Bukhari (SJU: St. John's University)H-Index: 15
Abstract null null Available clinical methods for heart failure (HF) diagnosis are expensive and require a high-level of experts intervention. Recently, various machine learning models have been developed for the prediction of HF where most of them have an issue of over-fitting. Over-fitting occurs when machine learning based predictive models show better performance on the training data yet demonstrate a poor performance on the testing data and the other way around. Developing a machine learnin...
#1Chinmayee Dora (I2IT: International Institute of Information Technology)H-Index: 4
#2Ram Narayana Patro (I2IT: International Institute of Information Technology)H-Index: 1
Last. Birendra Biswal (Gayatri Vidya Parishad College of Engineering)H-Index: 12
view all 5 authors...
Abstract Background Electroencephalogram (EEG) signals are obtained from the scalp surface to study various neuro-physiological functions of brain. Often, these signals are obscured by the other physiological signals of the subject from heart, eye and facial muscles. Hence, the successive applications of EEG are adversely affected. The wide spectrum and high amplitude variation of muscle artifact overlaps EEG both in spectral and temporal domain. Objective In this paper, an adaptive singular spe...
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