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AN INTERPRETABLE ARTIFICIAL NEURAL NETWORK-BASED PATIENT COUNSELING ALGORITHM FOR INDIVIDUALIZED INTRAUTERINE INSEMINATION (IUI) OUTCOMES Open

Zoran J. Pavlovic, Victoria S. Jiang, Steven Walczak, Papri Sarkar, Eduardo Hariton , et al. · 2023

A neural network analysis of the effect of high and low frailty index indicators on predicting elective surgery discharge destinations Open

Steven Walczak, Vic Velanovich · 2023

Background Frailty is frequently used by clinicians to help determine surgical outcomes. The frailty index, which represents the frequency of frailty indicators present in an individual, is one method for evaluating patient frailty to pred…

Predicting Estimated Blood Loss and Transfusions in Gynecologic Surgery Using Artificial Neural Networks Open

Steven Walczak, Emad Mikhail · 2022

This chapter explores valuating the efficacy of using artificial neural networks (ANNs) for predicting the estimated blood loss (EBL) and also transfusion requirements of myomectomy patients. All 146 myomectomy surgeries performed over a 6…

Predicting Crime and Other Uses of Neural Networks in Police Decision Making Open

Steven Walczak · 2021

Neural networks are a machine learning method that excel in solving classification and forecasting problems. They have also been shown to be a useful tool for working with big data oriented environments such as law enforcement. This articl…

MaLang: A Decentralized Deep Learning Approach for Detecting Abusive Textual Content Open

Pranav Kompally, Sibi Chakkaravarthy Sethuraman, Steven Walczak, Samuel Johnson, Meenalosini Vimal Cruz · 2021

Cyberbullying is a growing and significant problem in today’s workplace. Existing automated cyberbullying detection solutions rely on machine learning and deep learning techniques. It is proven that the deep learning-based approaches produ…

Predicting Estimated Blood Loss and Transfusions in Gynecologic Surgery Using Artificial Neural Networks Open

Steven Walczak, Emad Mikhail · 2020

This chapter explores valuating the efficacy of using artificial neural networks (ANNs) for predicting the estimated blood loss (EBL) and also transfusion requirements of myomectomy patients. All 146 myomectomy surgeries performed over a 6…

Prediction of perioperative transfusions using an artificial neural network Open

Steven Walczak, Vic Velanovich · 2020

ANNs can predict >75% of the patients who will require transfusion and 70% of those who will not. Increasing specificity to 80% still enables a sensitivity of almost 67%. The unique contribution of this research is the utilization of a sin…

Prophylactic antibiotic bundle compliance and surgical site infections: an artificial neural network analysis Open

Steven Walczak, Marbelly Davila, Vic Velanovich · 2019

A Text Analytic Approach to Classifying Document Types Open

Steven Walczak · 2017

Background: While it is commonly recognized that almost every work and research discipline utilize their own taxonomy, the language used within a specific discipline may also vary depending on numerous factors, including the desired effec…

Personality Type Effects on Perceptions of Online Credit Card Payment Open

Steven Walczak, Gary L. Borkan · 2015

Credit cards and the subsequent payment of credit card debt play a crucial role in e-commerce transactions. While website design effects on trust and e-commerce have been studied, these are usually coarse grained models. A more individuali…

A Heuristic Text Analytic Approach for Classifying Research Articles Open

Steven Walczak, Deborah L. Kellogg · 2015

Classification of research articles is fundamental to analyze and understand research literature. Underlying concepts from both text analytics and concept mining form a foundation for the development of a quantitative heuristic methodology…

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