Search Results - "Richter, Aaron N."

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…•A review of literature using analytical techniques to predict cancer risk is performed.•This research can improve patient outcomes and reduce healthcare…”
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A survey of open source tools for machine learning with big data in the Hadoop ecosystem by Landset, Sara, Khoshgoftaar, Taghi M., Richter, Aaron N., Hasanin, Tawfiq

“…With an ever-increasing amount of options, the task of selecting machine learning tools for big data can be difficult. The available tools have advantages and…”
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Efficient learning from big data for cancer risk modeling: A case study with melanoma by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance…”
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Sample size determination for biomedical big data with limited labels by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…The era of big data has produced vast amounts of information that can be used to build machine learning models. In many cases, however, there is a point where…”
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Survey of review spam detection using machine learning techniques by Crawford, Michael, Khoshgoftaar, Taghi M., Prusa, Joseph D., Richter, Aaron N., Al Najada, Hamzah

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Melanoma risk modeling from limited positive samples by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…The key to effective cancer treatment is early detection. Risk models built from routinely collected clinical data have the opportunity to improve early…”
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Survey of review spam detection using machine learning techniques by Crawford, Michael, Khoshgoftaar, Taghi M., Prusa, Joseph D., Richter, Aaron N., Al Najada, Hamzah

“…Online reviews are often the primary factor in a customer’s decision to purchase a product or service, and are a valuable source of information that can be…”
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Learning Curve Estimation with Large Imbalanced Datasets by Richter, Aaron N, Khoshgoftaar, Taghi M

“…Datasets for machine learning are constantly increasing in size, along with computational requirements for processing the data. A useful exercise for machine…”
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Building and Interpreting Risk Models from Imbalanced Clinical Data by Richter, Aaron N, Khoshgoftaar, Taghi M

“…As more clinical data becomes available for research, it is important to be able to build effective models and understand the predictions made from them. In…”
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Approximating Learning Curves for Imbalanced Big Data with Limited Labels by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…Labeling data for supervised learning can be an expensive task, especially when large amounts of data are required to build an adequate classifier. For most…”
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A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data by Richter, Aaron N., Khoshgoftaar, Taghi M., Landset, Sara, Hasanin, Tawfiq

“…Big data is a big business, and effective modeling of this data is key. This paper provides a comprehensive multidimensional analysis of various open source…”
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Efficient Modeling of User-Entity Preference in Big Social Networks by Richter, Aaron N., Crawford, Michael, Heredia, Brian, Khoshgoftaar, Taghi M.

“…Data generated by social media are frequently leveraged to build machine learning models that can accurately profile human behavior and sentiment. Twitter is a…”
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Predicting Melanoma Risk from Electronic Health Records with Machine Learning Techniques by Richter, Aaron N

“…Melanoma is one of the fastest growing cancers in the world, and can affect patients earlier in life than most other cancers. Therefore, it is imperative to be…”
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Modernizing Analytics for Melanoma with a Large-Scale Research Dataset by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…We present the Modernizing Analytics for MELanoma (MAMEL) dataset: a real-world, dermatology-specific research dataset specifically crafted to advance data…”
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Predicting sentinel node status in melanoma from a real-world EHR dataset by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…Melanoma is the fastest growing cancer worldwide, and 1 in 50 Americans will develop it in their lifetime. Sentinel lymph node (SLN) metastasis is one of the…”
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Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques by Richter, Aaron N., Khoshgoftaar, Taghi M.

“…While cancer treatments are constantly advancing, there is still a real risk of relapse after potentially curative treatments. At the risk of adverse side…”
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