A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living Pattern Recognition, 48 (2015), pp. 628-641 View PDFView articleView in ScopusGoogle Sch
A revealing and surprising look at the ways that aggressive consumer advertising and tracking, already pervasive online, are coming to a retail store near you By one expert€TMs prediction, within twenty years half of Americans will have body implants that tell retailers how they feel about ...
Finally, we propose a new interactive bot available for users that relies on the best-performing models evaluated in the previous steps. The experiments have been conducted using two medical datasets for disease prediction consisting of more than 100 symptoms associated with several diagnoses....
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer-Verlag, 2009). George, M.S. et al. Daily repetitive transcranial magnetic stimulation (rTMS) improves mood in depression. Neuroreport 6, 1853–1856 (1995). Article CAS PubMed Google Scholar Pascual-Leone, A...
Unsupervised and supervised survival analysis and prediction Unsupervised hierarchal clustering using the previously described prognostic miRNA profiles in the MGH and TARGET datasets was performed with the centered correlation and average linkage method51 and resulting groups were then analyzed for survival di...
The individual assemblies were used for gene prediction at a later stage. All RNA-Seq assem- blies were quality filtered using Transrate to reduce the probability of mis-assembled transcripts. Predicted cod- ing sequences were generated using TransDecoder (with PFAM and BLAST guides). Diamond ...
those features that did not have a meaningful effect on the dependent variable or prediction of output. Then, we deployed exhaustive feature selection, which aims at finding the best-performing feature subset by searching across all possible feature combinations (a brute-force method) until the desi...
Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics. 2006;7(1):62. 134. Holt C, Yandell M. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinformatics. ...
Adding the percentage of VDAC1+CPT1a+ myeloid cells, pDCs, and H3K27Me3+VDAC1+CD4+ improved prediction of COVID-19 severity compared with basic clinical information (Figure S7C), highlighting the important contribution of the immune cell populations identified to disease severity. This model ...
target and source have same primary metabolite that is responsible for toxicity; metabolism rate data (usually experimentally derived) Variable depending on knowledge of metabolites Identify metabolites from experimental studies or in silico prediction; (rate data may be available from experimental studies)...