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3. Detection of Cognitive States from fMRI data using Machine Learning Techniques

Author

Singh, Vishwajeet, Miyapuram, K. P., and Bapi, Raju S.

Subjects
Neuroscience: Brain Imaging, Computer Science: Machine Learning, Brain Imaging, Machine Learning
Abstract

Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cognitive state. We consider the inverse problem of detecting the cognitive state of a human subject based on the fMRI data. We have explored classification techniques such as Gaussian Naive Bayes, k-Nearest Neighbour and Support Vector Machines. In order to reduce the very high dimensional fMRI data, we have used three feature selection strategies. Discriminating features and activity based features were used to select features for the problem of identifying the instantaneous cognitive state given a single fMRI scan and correlation based features were used when fMRI data from a single time interval was given. A case study of visuo-motor sequence learning is presented. The set of cognitive states we are interested in detecting are whether the subject has learnt a sequence, and if the subject is paying attention only towards the position or towards both the color and position of the visual stimuli. We have successfully used correlation based features to detect position-color related cognitive states with 80% accuracy and the cognitive states related to learning with 62.5% accuracy.

Published
2007

15. A Review of the Design and Axial Capacity Calculation Practices for Helical Piles

Author

Debnath, Arnab, Singh, Vishwajeet. P., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Jose, Babu T., editor, Sahoo, Dipak Kumar, editor, Shin, Eun Chul, editor, Choudhury, Deepankar, editor, Joseph, Anil, editor, and Pai, Rahul R., editor

Published
2024
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29. Early bladder dysfunction after vesicovaginal fistula repair: A prospective comparative analysis of transvaginal, open, and laparoscopic abdominal approaches.

Author

Anand, Madhur, Kumar, Manoj, Jain, Mayank, Gupta, Amber, Kumar, Abhijeet, Singh, Bhupendra Pal, Singh, Vishwajeet, and Goel, Apul

Subjects
VESICOVAGINAL fistula, BLADDER diseases, URINARY organs, POSTOPERATIVE period, LAPAROSCOPIC surgery
Abstract

Introduction: We aim to compare the clinical and urodynamic profile of lower urinary tract symptoms (LUTS) in patients undergoing laparoscopic, open transabdominal, and laparoscopic transabdominal vesicovaginal fistulae (VVF) repair at 3 months of repair, that is, in early postoperative period. Materials and Methods: Fifty‐one consecutive patients with endoscopically confirmed VVF were enrolled in our study over 2 years. Malignant fistulae, radiation‐induced, and complex fistulae were excluded after cross‐sectional imaging. All patients underwent a postoperative assessment for the success of the repair. Then at 3 months, they completed the American Urological Association Symptom Score questionnaire and underwent a dual channel pressure‐flow urodynamic study. The results of transvaginal, laparoscopic, and open transabdominal repairs were compared. Results: All patients belonged to the Indian Caucasian race. The mean age was 35.43 ± 6.63 years. Thirty‐two patients had supratrigonal and 19 had trigonal fistulae. Laparoscopic transabdominal repair was done in 15 patients, open transabdominal repair in 22 patients, and transvaginal repair in 14 patients. Forty‐six patients reported some LUTS at a median follow‐up of 5.83 ± 2.37 months postoperatively. Only 18 (35.2%) of these patients had moderate to severe symptoms The postoperative bladder dysfunction rates in open transabdominal, transvaginal and laparoscopic transabdominal groups were 36.4%, 28.6%, and 20%, respectively. Twenty‐seven patients (52.9%) had some urodynamic abnormality, that is, small capacity (5), high voiding pressures (14), genuine stress incontinence (3), and poor compliance (3). Bladder capacity was a significant predictor of bladder dysfunction in our patients. Conclusions: In our study, all three surgical approaches were associated with bladder dysfunction, however, it was the least in the laparoscopic transabdominal approach. Postoperative bladder capacity is a significant predictor of bladder dysfunction. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Prevalence and clinical significance of deep vein thrombosis in Hispanic patients with acute pulmonary embolism.

Author

Murguia, Adrian Rojas, Prakash, Swathi, Segovia, Fernando, Ayvali, Fatih, Brockman, Michael, Nadella, Sahithi, Singh, Vishwajeet, Dwivedi, Alok Kumar, Rajachandran, Manu, Mukherjee, Debabrata, and Nickel, Nils P

Subjects
PULMONARY embolism, RISK assessment, DOPPLER ultrasonography, VENOUS thrombosis, HISPANIC Americans, COMPUTED tomography, RETROSPECTIVE studies, DESCRIPTIVE statistics, HEART failure, HEMODYNAMICS, SEVERITY of illness index, LONGITUDINAL method, MEDICAL records, ACQUISITION of data, CONFIDENCE intervals
Abstract

The prevalence of concomitant deep vein thrombosis (DVT) and its impact on 30-day outcomes in Hispanic patients with acute pulmonary embolism (PE) is unknown. We retrospectively studied a cohort of Hispanic patients admitted for acute PE to determine the relationship of concomitant DVT to clot burden on chest computer tomography (CT), right heart strain, and 30-day mortality. We identified 391 patients admitted with acute PE; 168 (42.9%) had concomitant DVTs on admission; 39 patients (9.9%) died during the 30-day follow-up: 12 patients without concomitant DVT and 27 with concomitant DVT, respectively (p <.001). The presence of a proximal DVT independently predicted 30-day mortality even after adjusting for age, gender and admission PE severity index scores (PESI) (hazard ratio [HR] 2.0; 95% confidence interval [CI]: 1.4-3.0, p =.001). Proximal DVTs remained a significant predictor of 30-day mortality in patients with low and intermediate PESI scores (HR 2.5; 95% CI: 1.1-6.0, p =.035). The prevalence of concomitant DVT in Hispanic patients presenting with acute DVT is relatively lower than other ethnic groups. However, a proximal location of a DVT is of significant prognostic relevance. Hispanic patients with acute PE should routinely undergo compression doppler ultrasonography (CDUS) of the lower extremities. [ABSTRACT FROM AUTHOR]

Published
2024
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31. The UK foot and ankle COVID-19 national (FAlCoN) audit – Regional variations in COVID-19 infection and national foot and ankle surgical activity

Author

Harb, Ziad, Richardson, Ruth, Gadd, Richard, Kerr, Alexander, Clay, William, Mallick, Arijit, Bhargava, Amit, Tiruveedhula, Madhu, Walls, Andrew, O'Flaherty, Maurice, Craig, Julie, Dawson, Daniel, McCaughey, Philip, Crean, Jonathan, Ayyasamy, Brijesh, Prasad, Pradeep, Ansnd, Anoop, Tarar, Yasir, Choo, Xin Yin, Yousufuddin, Shaik, Stone, Andrew, Amer, Mohammed, Haarer, Francesca, Barrow, Tom, Singh, Vishwajeet, Junaid, Sayani, Houssain, Natasha, Dhukaram, Vivek, Elbayyouk, Khalil, Abiddin, Zain ul, Salih, Samir, Fong, Angus, Arora, Abhishek, Louette, Luc, Faria, Giles, Smith, Andrew, Aithal, Shivashanker, Palihawadana, Dhanushka, Pir-Siahbazy, Ramtin, Zubairy, Aamir, Rose, Barry, McCormack, Annie, Vega-Poblete, Maira, Wahed, Karim, Malik, Khalid, Yousaf, Sohail, Sott, Andrea, Evangelidis, Dimosthenis, Hamilton, Paul, Abbott, Sarah, Naraen, Akarshan, Syed, Turab A, Benjamin, Biju, Ferreira, Catarina, Drampalos, Efstathios, Dasari, Kishore Kumar, Galhoum, Ahmed, Marsland, Daniel, Elliot, Robin, Chowdhury, Alex, Tareef, Tareq, Salim, Javed, Mishra, Viren, Amanat, Suheil, Ray, Robbie, Kavarthapu, Venu, Ahluwalia, Raju, Shah, Rohi, Lyle, Shirley, Molloy, Andy, Currall, Verity, Hatzantonis, Catherine, Dixon, Joseph, Goff, Thomas, Eyre, Jason, Kheir, Ehab, Haendlmayer, Kurt, Demoulin, Erin, Ali, Zulfikar, Loughenbury, Faye, Mansoor, Sufyan, Butcher, Alexander, Bonner, Rory, Saha, Anamika, Mcknight, Gareth Ewan, Lokanathan, Prashan, Lees, Rupert, Harrison, Peter, Kelly, Andrew, Macdonald, Hamish, Slade, George, Clayton, Robert, Middleton, Scott, Oag, Erlend, Loveday, David T, Atkinson, Henry, Dalrymple, James, Zaveri, Amit, Jani, Priya, Fernandes, Ramon, Johnson-Lynn, Sarah, Robertson-McPartlin, Lynne, Alderton, Elizabeth, Townshend, Dave, Porter, Anna, McLaughlin, Nicole, Guiguis, John, Kurup, Harish, Vasukutty, Nijil, Wokhlu, Ashim, Ogunsola, Abidemi, Koc, Togay, Hodkinson, Simon, Jowett, Billy, Shamoon, Samer, Mustafa, Qamar, Stoneham, Adam, Duggleby, Luke, Teoh, Kar, Ali, Shahahoor, Islam, Raisa, Butler, Mike, Brennan, Ciaran, Jennison, Toby, Karim, Tariq, Milner, Stephen, Mishra, Arya, Singh, Hemant, Haldar, Anil, Budair, Basil, MacKenzie, James, Dong, Huan, Prem, Hari, Wall, Rosemary, Dawe, Edward, Sexton, Sarah, O'Dowd-Booth, Christopher, Azeez, Sadeeq, Mavromatidou, Galini, Topliss, Claire, Makwana, Nilesh, Dass, Debashis, Abas, Sameera, Cheruvu, Manikandar Srinivas, Devany, Adam, Ieong, Edmund, Rudge, Ben, Kane, Prathamesh, Guha, Abhijit, Suen, Eric Ho Ming, Eldessouky, Amr, Saad, Ahmed Isam, Ali, Ibrahim, Hickey, Benjamin, Pillai, Anand, Islam, Amirul, Akbar, Zeeshan, Naylor, Tom, Khan, Umair, Jowett, Charlie, Mahmoud, Mohamed, Cryer, Gunay, Place, Stuart, Mason, Lyndon W, Malhotra, Karan, Houchen-Wollof, Linzy, and Mangwani, Jitendra

Published
2022
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40. Learning Discriminative Features using Encoder-Decoder type Deep Neural Nets

Author

Singh, Vishwajeet, Kumar, Killamsetti Ravi, and Eswaran, K

Subjects
Computer Science - Learning, Statistics - Machine Learning, I.5, I.5.3
Abstract

As machine learning is applied to an increasing variety of complex problems, which are defined by high dimensional and complex data sets, the necessity for task oriented feature learning grows in importance. With the advancement of Deep Learning algorithms, various successful feature learning techniques have evolved. In this paper, we present a novel way of learning discriminative features by training Deep Neural Nets which have Encoder or Decoder type architecture similar to an Autoencoder. We demonstrate that our approach can learn discriminative features which can perform better at pattern classification tasks when the number of training samples is relatively small in size., Comment: 12 pages, 8 figures and 8 tables

Published
2016

44. A Quick, High-Yield Biogenic Synthesis of Antibacterial AgNPs (Silver Nanoparticles) via Carica papaya Seeds.

Author

Singh, Anshu, Singh, Vishwajeet, Bharadwaj, Alok, Gaur, Ridhima, Agarwal, Smita, and Wahi, Nitin

Subjects
*SILVER nanoparticles, *PAPAYA, *ENTEROBACTER aerogenes, *SEEDS, *X-ray diffraction, *ANTIBACTERIAL agents
Abstract

Carica papaya seeds were used in this research for the synthesis of AgNPs. The production of silver nanoparticles was characterized using UV–Vis spectroscopy, FTIR, XRD and SEM-EDX analysis. The antibacterial activity of the prepared AgNPs was evaluated by the Kirby–Bauer disc diffusion method with the antibacterial activity of different compounds against Bacillus aerogenes. UV–Vis spectral peaks are found at 8–18 nm. SEM and TEM analysis revealed several spherical structures between 10 nm and 50 nm. XRD analysis also confirmed its 50 nm size. Experimental data revealed that AgNPs inhibited bacterial growth. This study shows that papaya seed extract contributes to the bioreduction and stabilization of the synthesized silver nanoparticles. [ABSTRACT FROM AUTHOR]

Published
2025
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48. Some Theorems for Feed Forward Neural Networks

Author

Eswaran, K. and Singh, Vishwajeet

Subjects
Computer Science - Neural and Evolutionary Computing, 62M45
Abstract

In this paper we introduce a new method which employs the concept of "Orientation Vectors" to train a feed forward neural network and suitable for problems where large dimensions are involved and the clusters are characteristically sparse. The new method is not NP hard as the problem size increases. We `derive' the method by starting from Kolmogrov's method and then relax some of the stringent conditions. We show for most classification problems three layers are sufficient and the network size depends on the number of clusters. We prove as the number of clusters increase from N to N+dN the number of processing elements in the first layer only increases by d(logN), and are proportional to the number of classes, and the method is not NP hard. Many examples are solved to demonstrate that the method of Orientation Vectors requires much less computational effort than Radial Basis Function methods and other techniques wherein distance computations are required, in fact the present method increases logarithmically with problem size compared to the Radial Basis Function method and the other methods which depend on distance computations e.g statistical methods where probabilistic distances are calculated. A practical method of applying the concept of Occum's razor to choose between two architectures which solve the same classification problem has been described. The ramifications of the above findings on the field of Deep Learning have also been briefly investigated and we have found that it directly leads to the existence of certain types of NN architectures which can be used as a "mapping engine", which has the property of "invertibility", thus improving the prospect of their deployment for solving problems involving Deep Learning and hierarchical classification. The latter possibility has a lot of future scope in the areas of machine learning and cloud computing., Comment: 15 pages 13 figures

Published
2015
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50. Amplified Fragment Length Polymorphism based Genetic Diversity of Tropical Legume: Lablab purpureus var. typicus.

Author

Singh, Vishwajeet, Wahi, Nitin, Garg, Gunjan, and Singh, Anshu

Subjects
*AMPLIFIED fragment length polymorphism, *CLIMBING plants, *LEGUME farming, *GENETIC variation, *GENE mapping
Abstract

Background: Lablab purpureus L. is a legume appropriate to grow in tropical environment as it is adaptable to a broad temperature spectrum, rainfall and altitudes. It develops well under humid and warm conditions at temperatures ranging between 18oC and 30oC. It is a drought hardy crop grown in humid and semi-arid regions. The species is propagated by seed and can be sown alone or intercropped; planted near hedges or near other less leafy plants to climb on. Lablab purpureus L. has a flowering response of shortday, with early and late flowering types. Some landraces flower after sowing as early as 55 days. It is predominantly self pollinated although some out crossing is known to occur. Methods: In this study, Lablab purpureus L. genetic diversity were analyzed utilizing AFLP markers on ten Indian Lablab purpureus L. accessions at Department of Botany, Bundelkhand University, Jhansi during 2019-20. Five primers set were used for checking the diversity in Lablab purpureus L. and the marker performance were measured by using 4 parameters i.e. PIC, Mean resolving Power, Resolving Power and MI. Result: A total of 52 bands were generated, of which 45 bands (88.46%) were polymorphic which varies from 6 (M-CAT/E-ACT ) to 13 (M-CAC/E-ACC, M-CAC/E-ACT) with mean of 9.00 bands per primer. The PIC value ranges between 0.55 and 0.76 with a mean value of 0.64. The average value of matrix index is 3.04. Higher the MI, better the marker is. The value of RP ranges between 2.60 and 7.80 with a mean value of 4.68. In the UPGMA dendrogram, the 10 accessions were separated into two main clusters with all the primers used. In this study, we have shown that molecular markers can be used successfully to understand the genetic structure of the accessions of Lablab purpureus L. and identified a series of sequence-specific markers that potentially could be used in Lablab purpureus L. genetic mapping analyses. Since Lablab purpureus L. has been considered as a promising crop because of its wide spectrum of adaptability to different ecological conditions than other legumes, participatory evaluation at an early breeding stage could shape the variety being developed to increase the productivity and other traits as well as for utilization as food. [ABSTRACT FROM AUTHOR]

Published
2024
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