32 citations · 44 across the 19 of their papers we have counts for
6 papers · 1 filter
Predicting High-Risk Colorectal Polyps in African Americans Using Pre-Colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation
Basheer Qolomany, Mrinalini Deverapall, Adeyinka Laiyemo +5
Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing interest in whether non-invasive features av…
Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments
Manish Osti, Aashray Thakuri, Basheer Qolomany +1
This study presents Weighted Sampled Split Learning (WSSL), an innovative framework tailored to bolster privacy, robustness, and fairness in distributed machine learning systems. U…
CovidMis20: COVID-19 Misinformation Detection System on Twitter Tweets using Deep Learning Models
Aos Mulahuwaish, Manish Osti, Kevin Gyorick +3
Online news and information sources are convenient and accessible ways to learn about current issues. For instance, more than 300 million people engage with posts on Twitter global…
Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
Ihab Mohammed, Shadha Tabatabai, Ala Al-Fuqaha +4
Machine Learning (ML), and Deep Learning (DL) in particular, play a vital role in providing smart services to the industry. These techniques however suffer from privacy and securit…
Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
Basheer Qolomany, Kashif Ahmad, Ala Al-Fuqaha +1
Most of the research on Federated Learning (FL) has focused on analyzing global optimization, privacy, and communication, with limited attention focusing on analyzing the critical…
Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services
Basheer Qolomany, Ihab Mohammed, Ala Al-Fuqaha +2
With Machine Learning (ML) services now used in a number of mission-critical human-facing domains, ensuring the integrity and trustworthiness of ML models becomes all-important. In…