90 citations · 178 across the 10 of their papers we have counts for
11 papers
Pattern Recognition in Vital Signs Using Spectrograms
Sidharth Srivatsav Sribhashyam, Md Sirajus Salekin, Dmitry Goldgof +3
Spectrograms visualize the frequency components of a given signal which may be an audio signal or even a time-series signal. Audio signals have higher sampling rate and high variab…
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders
Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof +2
Identifying who is infected with the Covid-19 virus is critical for controlling its spread. X-ray machines are widely available worldwide and can quickly provide images that can be…
Multimodal Spatio-Temporal Deep Learning Approach for Neonatal Postoperative Pain Assessment
Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof +3
The current practice for assessing neonatal postoperative pain relies on bedside caregivers. This practice is subjective, inconsistent, slow, and discontinuous. To develop a reliab…
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset
Lawrence O. Hall, Rahul Paul, Dmitry B. Goldgof +1
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X…
First Investigation Into the Use of Deep Learning for Continuous Assessment of Neonatal Postoperative Pain
Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof +3
This paper presents the first investigation into the use of fully automated deep learning framework for assessing neonatal postoperative pain. It specifically investigates the use…
Harnessing the Power of Deep Learning Methods in Healthcare: Neonatal Pain Assessment from Crying Sound
Md Sirajus Salekin, Ghada Zamzmi, Rahul Paul +4
Neonatal pain assessment in clinical environments is challenging as it is discontinuous and biased. Facial/body occlusion can occur in such settings due to clinical condition, deve…
Multi-Channel Neural Network for Assessing Neonatal Pain from Videos
Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof +3
Neonates do not have the ability to either articulate pain or communicate it non-verbally by pointing. The current clinical standard for assessing neonatal pain is intermittent and…
Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop
Saeed S. Alahmari, Dmitry Goldgof, Lawrence O. Hall +3
Lack of enough labeled data is a major problem in building machine learning based models when the manual annotation (labeling) is error-prone, expensive, tedious, and time-consumin…
A method to Suppress Facial Expression in Posed and Spontaneous Videos
Ghada Zamzmi, Gabriel Ruiz, Matthew Shreve +3
We address the problem of suppressing facial expressions in videos because expressions can hinder the retrieval of important information in applications such as face recognition. T…
Neonatal Pain Expression Recognition Using Transfer Learning
Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi +1
Transfer learning using pre-trained Convolutional Neural Networks (CNNs) has been successfully applied to images for different classification tasks. In this paper, we propose a new…
Machine-based Multimodal Pain Assessment Tool for Infants: A Review
Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi +2
Bedside caregivers assess infants' pain at constant intervals by observing specific behavioral and physiological signs of pain. This standard has two main limitations. The first li…