https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 Prediction of plant promoters based on hexamers and random triplet pair analysis https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31579 Wed 11 Apr 2018 16:51:42 AEST ]]> Improvement of liver segmentation by combining high order statistical texture features with anatomical structural features https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28738 Wed 11 Apr 2018 12:42:02 AEST ]]> A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38139 Wed 04 Aug 2021 15:42:39 AEST ]]> Automated detection of pneumoconiosis with multilevel deep features learned from chest x-ray radiographs https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49430 Tue 14 Nov 2023 13:23:44 AEDT ]]> A Spatial Data-Driven Approach for Mineral Prospectivity Mapping https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53041 Tue 14 Nov 2023 11:50:37 AEDT ]]> Landslide susceptibility assessment based on clustering analysis and support vector machine https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36462 Tue 12 May 2020 13:50:43 AEST ]]> A novel level set segmentation algorithm for computer-aided hepatic surgical planning https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34009 Thu 31 Jan 2019 10:14:09 AEDT ]]> Landslide susceptibility prediction using an incremental learning Bayesian Network model considering the continuously updated landslide inventories https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52223 Thu 05 Oct 2023 10:30:27 AEDT ]]> Automatic power load event detection and appliance classification based on power harmonic features in nonintrusive appliance load monitoring https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19076 Sat 24 Mar 2018 08:05:21 AEDT ]]> Feedback analysis of tunnel construction using a hybrid arithmetic based on support vector machine and particle swarm optimisation https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18146 Sat 24 Mar 2018 08:04:45 AEDT ]]> An approach of household power appliance monitoring based on machine learning. https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16337 Sat 24 Mar 2018 07:58:01 AEDT ]]> Comparisons of machine learning methods for electricity regional reference price forecasting. https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16333 Sat 24 Mar 2018 07:58:00 AEDT ]]> Accurate object segmentation using novel active shape and appearance models based on support vector machine Learning https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18499 Sat 24 Mar 2018 07:51:21 AEDT ]]> An automatic rib segmentation method on x-ray radiographs https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27128 Sat 24 Mar 2018 07:41:35 AEDT ]]> Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25812 postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.]]> Sat 24 Mar 2018 07:34:35 AEDT ]]> Effects of training datasets on both the extreme learning machine and support vector machine for target audience identification on Twitter https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27403 Sat 24 Mar 2018 07:34:09 AEDT ]]> Landslide susceptibility mapping based on self-organizing-map network and extreme learning machine https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30365 Sat 24 Mar 2018 07:26:47 AEDT ]]> Personalized recommendation system based on support vector machine and particle swarm optimization https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23386 Sat 24 Mar 2018 07:13:57 AEDT ]]> Automatic liver segmentation from CT images by combining statistical models with machine learning https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23412 Sat 24 Mar 2018 07:13:53 AEDT ]]> Landslide susceptibility prediction considering regional soil erosion based on machine-learning models https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40728 Mon 18 Jul 2022 11:48:21 AEST ]]> Prediction of groundwater levels using evidence of chaos and support vector machine https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34441 Mon 11 Mar 2019 13:37:22 AEDT ]]> Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35128 Fri 21 Jun 2019 12:52:57 AEST ]]> Using an improved relative error support vector machine for body fat prediction https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47227 Fri 16 Dec 2022 11:26:23 AEDT ]]> A comparative study of different machine learning methods for reservoir landslide displacement prediction https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49126 Fri 05 May 2023 11:53:47 AEST ]]>