Researchers imaging data along with image-processing algorithms in order to develop a set of candidate image features that can be used to develop a quantitative description of xenografted colorectal chronic tumor hypoxia. These features were used to develop a spatiotemporal logical expression as well as a way to formulate a linear regression function that uses all of the image features to describe...

This dataset was compiled as part of the Graphic User Interface for deep brain stimulation (DBS) Evaluation (GUIDE) study, a multicenter prospective pilot study designed to assess whether a computer-guided model could provide equally effective and more expeditious programming results when compared with the traditional, clinical deduced method of DBS programming of the subthalamic nucleus (STN). 26...

Neuroanatomical Age Prediction Using R (NAPR) is a framework that provides network-based access to predictive modeling software running on a persistent Amazon Web Services (AWS) computing instance. External users may estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. The model was trained using healthy control...

The MIDAS (Models of Infectious Disease Agent Study) Online Portal for COVID-19 Modeling Research is a collection of publicly-available COVID-19 resources to support dashboard monitoring, data processing, modeling, and visualization efforts. Collections listed in the portal include case counts and case line lists with documented metadata, peer-reviewed and non-peer-reviewed parameter estimates, and...

This dataset contains behavioral data assessing the sensitivity of five human subjects (one female and four male) to higher-order moments of motion as applied to random dot kinematograms. The dots were manipulated by probability distributions that systematically differed in their mean, variance, skewness, or kurtosis. Following training sessions where they reached at least 80% accuracy, subjects were...

This record describes a cleaned dataset and supporting R code for a series of statistical models that were developed with data from the 2003–2004 National Health and Nutrition Examination Survey (NHANES) to assess the effects of environmental risk factors on continuous, categorical (binary), time-to-event, and longitudinal outcomes. Investigators utilized a unified partial-linear single-index (PLSI)...

This dataset assesses the influence of timescale on the processing of visual stimuli. Following training sessions where they reached at least 76% accuracy, five human subjects (four male and one female) were presented with the following task: brief samples of a contrast pattern were presented on screen for 200 ms, followed by a pause before the subjects were prompted to match the samples to one of...

This data collection includes neural recordings obtained from the visual cortex (V1 and V2) and prearcurate gyrus (8Ar) of macaque monkeys (Macaca nemestrina and Macaca mulatta) during a direction discrimination task and code for replicating the modeling of neural representations. 96-channel microelectrode Utah arrays were implanted across the border of the V1 and V2 visual cortices of Macaca nemestrina....

NYUTron is a large language model-based system that was developed with the objective of integrating clinical workflows centered around structured and unstructured notes and placing electronic orders in real time. The development team queried electronic health records from all NYU Langone facilities to generate two types of datasets: pre-training datasets ("NYU Notes", "NYU Notes–Manhattan", "NYU Notes–Brooklyn")...

This study investigated how psychophysical reverse correlation may be used to understand the sensory mechanisms and decision-making processes underlying goal-directed behavior. The investigators used simulation modeling to build variations of a drift diffusion model (DDM) to develop a quantitative measure of psychophysical kernels on the integration of sensory input over time (non-decision time) until...