Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data
Authors: Zhaobin Kuang, James Thomson, Michael Caldwell, Peggy Peissig, Ron Stewart, David Page
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | For evaluation, we use the proposed methods to search for drugs that can lower Fasting Blood Glucose (FBG) level in the Marshfield Clinic EHR. Experimental results suggest that the proposed methods are capable of rediscovering drugs that can lower FBG level as well as identifying some potential blood sugar lowering drugs in the literature. |
| Researcher Affiliation | Collaboration | University of Wisconsin-Madison1,6, Morgridge Institute for Research2,5, Marshfield Clinic3,4 |
| Pseudocode | Yes | Algorithm 1 Blockwise MinimizationRequire: y, X, Z, Dδ, λ1 > 0, λ2 > 0 Ensure: solution β, t1: Initialize t(0) = 0, solveβ(0) = arg min2 + λ1 kβk1 .2: for k 0, 1, 2, do 3: Solve the t-Step in (12) for t(k+1)4: Solve the β-Step in (13) for β(k+1)5: if stop criterion satisfied then 6: return β(k+1), t(k+1)7: end if 8: end for |
| Open Source Code | No | The paper mentions using existing R packages (genlasso, glmnet) but does not provide concrete access to the source code for the specific methodology described in this paper. |
| Open Datasets | No | EHRs from Marshfield Clinic are used in our experiments. 64515 patients are admitted in the cohort with 219306 FBG measurements in total. 2980 drugs are considered in the experments. |
| Dataset Splits | No | The paper mentions using Bayesian Information Criterion (BIC) for model selection, implying a validation process, but does not provide specific dataset split information (percentages, sample counts, or predefined splits) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper mentions using the 'genlasso' and 'glmnet' packages in R, but does not provide specific version numbers for these software components or the R environment itself. |
| Experiment Setup | Yes | The pairs of λ1 and λ2 are chosen in a way to ensure that approximately two hundred drugs or more are selected. We use Bayesian Information Criterion (BIC) [Zou et al., 2007; Tibshirani and Taylor, 2011] to select the best model from the eight candidates... In our experiments, we set δ = 4 years. |