Saras Saraswathi
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Performance enhancement of extreme learning machine for multi-category sparse data classification problems
S Suresh, S Saraswathi, N Sundararajan
Engineering Applications of Artificial Intelligence 23 (7), 1149-1157, 2010
ICGA-PSO-ELM approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented
S Saraswathi, S Sundaram, N Sundararajan, M Zimmermann, ...
IEEE/ACM Transactions on Computational Biology and Bioinformatics 8 (2), 452-463, 2010
Detection of onset of Alzheimer's disease from MRI images using a GA-ELM-PSO classifier
S Saraswathi, BS Mahanand, A Kloczkowski, S Suresh, N Sundararajan
2013 fourth international workshop on computational intelligence in medical …, 2013
The importance of slow motions for protein functional loops
A Skliros, MT Zimmermann, D Chakraborty, S Saraswathi, AR Katebi, ...
Physical biology 9 (1), 014001, 2012
A systematic review of childhood diabetes research in the Middle East region
S Saraswathi, S Al-Khawaga, N Elkum, K Hussain
Frontiers in endocrinology 10, 805, 2019
Protein secondary structure prediction using a small training set (compact model) combined with a Complex-valued neural network approach
S Rashid, S Saraswathi, A Kloczkowski, S Sundaram, A Kolinski
BMC bioinformatics 17, 1-18, 2016
The clinical and genetic characteristics of permanent neonatal diabetes (PNDM) in the state of Qatar
S Al‐Khawaga, I Mohammed, S Saraswathi, B Haris, R Hasnah, A Saeed, ...
Molecular genetics & genomic medicine 7 (10), e00753, 2019
Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction
S Saraswathi, JL Fernández-Martínez, A Kolinski, RL Jernigan, ...
Journal of molecular modeling 18, 4275-4289, 2012
Corneal nerve loss in children with type 1 diabetes mellitus without retinopathy or microalbuminuria
H Gad, B Al‐Jarrah, S Saraswathi, IN Petropoulos, G Ponirakis, A Khan, ...
Journal of diabetes investigation 11 (6), 1594-1601, 2020
Somatostatin analogues for the treatment of hyperinsulinaemic hypoglycaemia
B Haris, S Saraswathi, K Hussain
Therapeutic Advances in Endocrinology and Metabolism 11, 2042018820965068, 2020
In Silico Modeling of Human α2C-Adrenoreceptor Interaction with Filamin-2
M Pawlowski, S Saraswathi, HKB Motawea, MA Chotani, A Kloczkowski
PLoS One 9 (8), e103099, 2014
A SLC16A1 mutation in an infant with ketoacidosis and neuroimaging assessment: expanding the clinical spectrum of MCT1 deficiency
S Al-Khawaga, J AlRayahi, F Khan, S Saraswathi, R Hasnah, B Haris, ...
Frontiers in Pediatrics 7, 299, 2019
Multi-class BCGA-ELM based classifier that identifies biomarkers associated with hallmarks of cancer
V Sachnev, S Saraswathi, R Niaz, A Kloczkowski, S Suresh
BMC bioinformatics 16 (1), 1-12, 2015
Clinical features, epidemiology, autoantibody status, HLA haplotypes and genetic mechanisms of type 1 diabetes mellitus among children in Qatar
B Haris, I Ahmed, N Syed, H Almabrazi, S Saraswathi, S Al-Khawaga, ...
Scientific Reports 11 (1), 18887, 2021
Distinctive microbial signatures and gut-brain crosstalk in pediatric patients with coeliac disease and type 1 diabetes mellitus
P Singh, A Rawat, B Al-Jarrah, S Saraswathi, H Gad, M Elawad, ...
International Journal of Molecular Sciences 22 (4), 1511, 2021
Epidemiology, genetic landscape and classification of childhood diabetes mellitus in the State of Qatar
B Haris, S Saraswathi, S Al‐Khawaga, R Hasnah, A Saeed, ...
Journal of Diabetes Investigation 12 (12), 2141-2148, 2021
Multi-region risk-sensitive cognitive ensembler for accurate detection of attention-Deficit/Hyperactivity disorder
V Sachnev, S Suresh, N Sundararajan, BS Mahanand, MW Azeem, ...
Cognitive Computation 11, 545-559, 2019
Machine learning based ad-click prediction system
S Saraswathi, V Krishnamurthy, DVV Prasad, RK Tarun, S Abhinav, ...
Int J Eng Adv Technol 8 (6), 3646-3648, 2019
Protein secondary structure prediction using a fully complex-valued relaxation network
B Shamima, R Savitha, S Suresh, S Saraswathi
The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013
Particle swarm optimization: a powerful family of stochastic optimizers. Analysis, design and application to inverse modelling
JL Fernández-Martínez, E García-Gonzalo, S Saraswathi, R Jernigan, ...
Advances in Swarm Intelligence: Second International Conference, ICSI 2011 …, 2011
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Articles 1–20