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Do Deep Neural Networks Outperform Kernel Regression for Functional Connectivity Prediction of Behavior? [article]

Tong He, Ru Kong, Avram Holmes, Minh Nguyen, Mert Sabuncu, Simon B. Eickhoff, Danilo Bzdok, Jiashi Feng, B.T. Thomas Yeo
2018 bioRxiv   pre-print
Here, we compared the performance of three DNN architectures and a classical machine learning algorithm (kernel regression) in predicting individual phenotypes from whole-brain resting-state functional  ...  There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data.  ...  The entries of the RSFC matrices can then be used as features for predicting behavioral measures (e.g., fluid intelligence) in individual participants (Finn et al., 2015; Smith et al., 2015; Dubois and  ... 
doi:10.1101/473603 fatcat:mvey55qhergadgkrfedisy45zm

Mixed Machine Learning Approach for Efficient Prediction of Human Heart Disease by Identifying the Numerical and Categorical Features

Ghulab Ahmad, Shafiullah, Hira Fatima, Mohamed Abbas, Obaidur Rahman, Imdadullah, Mohammed Alqahtani
2022 Applied Sciences  
In this paper, a unique heart disease prediction model is proposed to predict heart disease correctly and rapidly using a variety of bodily signs.  ...  The manual analysis and prediction of a massive volume of data are challenging and time-consuming.  ...  Nu-Support Vector Classifier (Nu-SVC) The sole distinction between the Nu-support vector classifier and the support vector classifier is the Nu parameter, which regulates the number of support vectors.  ... 
doi:10.3390/app12157449 fatcat:3tyjma5qybbfpe6rjz5ctf5hri

Multivariate resting-state functional connectivity predicts response to cognitive behavioral therapy in obsessive–compulsive disorder

Nicco Reggente, Teena D. Moody, Francesca Morfini, Courtney Sheen, Jesse Rissman, Joseph O'Neill, Jamie D. Feusner
2018 Proceedings of the National Academy of Sciences of the United States of America  
We leveraged machine learning with cross-validation to assess the power of functional connectivity (FC) patterns to predict individual posttreatment OCD symptom severity.  ...  Pretreatment FC patterns within the default mode network and visual network significantly predicted posttreatment OCD severity, explaining up to 67% of the variance.  ...  This work was supported by a National Institute of Mental Health Grant (R01MH085900, to J.O. and J.D.F.). ClinicalTrials.gov identifier is NCT01368510.  ... 
doi:10.1073/pnas.1716686115 pmid:29440404 pmcid:PMC5834692 fatcat:rimgfbrygzebrezdqsiauvfxnu

Leveraging Big Data Analytics in Healthcare Enhancement: Trends, Challenges and Opportunities [article]

Arshia Rehman, Saeeda Naz, Imran Razzak
2020 arXiv   pre-print
It promises us the power of early detection, prediction, prevention and helps us to improve the quality of life.  ...  Due to the sheer size and availability of healthcare data, big data analytics has revolutionized this industry and promises us a world of opportunities.  ...  [291] recognized the Lung cancer using sensor-based wrist pulse signal processing with the technique of cubic support vector machine (CSVM).  ... 
arXiv:2004.09010v1 fatcat:ojysowdbdncsrdgpsvenksekyq

Brain network topology predicts participant adherence to mental training programs

Marzie Saghayi, Jonathan Greenberg, Christopher O'Grady, Farshid Varno, Muhammad Ali Hashmi, Bethany Bracken, Stan Matwin, Sara W. Lazar, Javeria Ali Hashmi
2020 Network Neuroscience  
This study tests whether configurations of brain connections in resting-state fMRI scans can be used to predict adherence to two programs, a meditation program and creative writing program.  ...  , and in the writing program, adherence was predicted by network neighbourhood of frontal and temporal regions.  ...  MRI data processing Preprocessing of resting state data was performed using in house BASH scripts that used function libraries from FMRIB Software Library v5.0 (FSL, University of Oxford, United Kingdom  ... 
doi:10.1162/netn_a_00136 pmid:32885114 pmcid:PMC7462432 fatcat:5xlhbd7mjzdvhht5ggfh65fg6y

Towards the Digitalisation of Porous Energy Materials: Evolution of Digital Approaches for Microstructural Design

Zhiqiang Niu, Valerie Pinfield, Billy Wu, Huizhi Wang, Kui Jiao, Dennis Y. C. Leung, Jin Xuan
2021 Energy & Environmental Science  
Porous energy materials are essential components of many energy devices and systems, the development of which have been long plagued by two main challenges. The first is the 'curse of...  ...  Acknowledgements The authors would like to acknowledge the support of the Royal Society -K. C.  ...  Science Foundation of China (51861130359) and the UK Royal Society (NAF\R1\180146), the Faraday Institution Multi-Scale Modelling project ((EP/S003053/1, grant number FIRG003), and the support from Engineering  ... 
doi:10.1039/d1ee00398d fatcat:tqqvy4vbs5gkdfn4x6frrosxuu

Proceedings Combined

2021 2021 International Conference on Applied and Engineering Mathematics (ICAEM)  
This research focuses on accurately classify tumors from MRI images using multiple Segmentation algorithms to overcome the slight chance of miss classification Error.  ...  So, extracting useful information, segment an image correctly, classify an image, and accurately predict the result, not an easy task.  ...  Classification classifies data (feature vector) in different classes and help generate modal while training and later help in predicting result in future.  ... 
doi:10.1109/icaem53552.2021.9547090 fatcat:zuqmi7a65jbxbmmjigp4v7gzsm

Brain Structure in Young and Old East Asians and Westerners: Comparisons of Structural Volume and Cortical Thickness

Michael Wei Liang Chee, Hui Zheng, Joshua Oon Soo Goh, Denise Park, Bradley P. Sutton
2011 Journal of Cognitive Neuroscience  
These findings were replicated using voxel-based morphometry applied to the same data set.  ...  ■ There is an emergent literature suggesting that East Asians and Westerners differ in cognitive processes because of cultural biases to process information holistically (East Asians) or analytically (  ...  Acknowledgments This work was supported by the BMRC (04/1/36/19/372) and the STaR award awarded to Michael Chee as well as by the National Institute on Aging, grant nos. R01 AGO15047 and R01AGO60625-  ... 
doi:10.1162/jocn.2010.21513 pmid:20433238 pmcid:PMC3361742 fatcat:g4sopue5y5gljn2e2pwi6tklui

Abstracts from Hydrocephalus 2019: The Eleventh Meeting of the International Society for Hydrocephalus and Cerebrospinal Fluid Disorders

2019 Fluids and Barriers of the CNS  
Fluids Barriers CNS 2019, 16(Suppl 3):36 • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data  ...  This study attempted to use a machine learning framework engine to classify CT images of hydrocephalus patients.  ...  with iNPH and sNPH by using 4D flow MRI.  ... 
doi:10.1186/s12987-019-0156-3 pmid:31801566 pmcid:PMC6894103 fatcat:32qfjodifffjzl22ktvnm3uq7m

2014 Index IEEE Transactions on Medical Imaging Vol. 33

2014 IEEE Transactions on Medical Imaging  
Classification of Dynamic Contrast Enhanced MR Images of Cervical Cancers Using Texture Analysis and Support Vector Machines.  ...  ., +, TMI June 2014 1390-1400 Classification of Dynamic Contrast Enhanced MR Images of Cervical Cancers Using Texture Analysis and Support Vector Machines.  ...  MRI Upsampling Using Feature-Based Nonlocal Means Approach. Jafari-Khouzani, K., 1969 -1985 Numerical Surrogates for Human Observers in Myocardial Motion Evaluation From SPECT Images.  ... 
doi:10.1109/tmi.2014.2386278 fatcat:poarfhfto5bm5mhfl7ugwtw4xy

ESGAR 2021 Book of Abstracts

2021 Insights into Imaging  
Conclusion: The present study provides additional support for the routine use of template reports to improve imaging reporting standards in colon cancer.  ...  Sironi 1 ; 1 Milan/IT, 2 Monza/IT Purpose: To evaluate the accuracy of the bioimpedance vector analysis (BIVA) in predicting pancreatic steatosis (PS) and development of postoperative pancreatic fistula  ... 
doi:10.1186/s13244-021-01015-4 pmid:34121138 fatcat:tkresswhfncdjaw4yl62tjbnda

Surgical Data Science - from Concepts toward Clinical Translation

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park (+39 others)
2021 Medical Image Analysis  
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery.  ...  of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics.  ...  The scikit-learn library in Python is the most widely used framework for MLbased classification, regression and clustering using non-DL models such as Support Vector Machines (SVMs), decision trees and  ... 
doi:10.1016/j.media.2021.102306 pmid:34879287 pmcid:PMC9135051 fatcat:4n27fogyqndghlc2e54h7uohgq

Medical image analysis: progress over two decades and the challenges ahead

J.S. Duncan, N. Ayache
2000 IEEE Transactions on Pattern Analysis and Machine Intelligence  
AbstractÐThe analysis of medical images has been woven into the fabric of the Pattern Analysis and Machine Intelligence (PAMI) community since the earliest days of these Transactions.  ...  Examples of these include: the types of image information that are acquired, the fully three-dimensional image data, the nonrigid nature of object motion and deformation, and the statistical variation  ...  Analysis and Machine Intelligence.  ... 
doi:10.1109/34.824822 fatcat:csqincxgozelphrz62ncrexqo4

Surgical Data Science – from Concepts toward Clinical Translation [article]

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park (+38 others)
2021 arXiv   pre-print
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery.  ...  of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics.  ...  The scikit-learn library in Python is the most widely used framework for MLbased classification, regression and clustering using non-DL models such as Support Vector Machines (SVMs), decision trees and  ... 
arXiv:2011.02284v2 fatcat:i5mq42uevjfxjmji5xdap3kgse

Objective evaluation of vowel pronunciation

Mark J. Bakkum, Reinier Plomp, Louis C. W. Pols
1991 Journal of the Acoustical Society of America  
Estimation of amounts of gas hydrate in marine sediments using amplitude reduction of seismic reflections. William P.  ...  Even with this admittedly low vertical resolution, the velocity above the BSR is at least 2000 m/s in an approximately 200-m zone, while the predicted velocity based on the extrapolation of regional gradients  ...  Plans for the next meetings of ISO/TC43 (in Australia in December 1991 ), and for IEC/TC 29 (in New Zealand, from 25-29 November 1991 } will be discussed.  ... 
doi:10.1121/1.2029328 fatcat:qntsmkrqkjbkpaxn35nuxutuaa
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