An Empirical Evaluation of Machine Learning Techniques for Chronic Kidney Disease Prophecy. - Bilal Khan 003; Rashid Naseem; Fazal Muhammad; Ghulam Abbas 002; Sunghwan Kim 001 (IEEE Access, 2020)

Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects. - Rashid Naseem; Bilal Khan 003; Arshad Ahmad 002; Ahmad Almogren; Saima Jabeen; Bashir Hayat; Muhammad Arif Shah (Complex., 2020)

Analysis of Tree-Family Machine Learning Techniques for Risk Prediction in Software Requirements. - Bilal Khan 003; Rashid Naseem; Iftikhar Alam; Inayat Khan; Hisham Alasmary; Taj Rahman (IEEE Access, 2022)

Exploring the Landscape of Automatic Text Summarization: A Comprehensive Survey. - Bilal Khan 003; Zohaib Ali Shah; Muhammad Usman 011; Inayat Khan; Badam Niazi (IEEE Access, 2023)

Machine Learning-Based Models for Magnetic Resonance Imaging (MRI)-Based Brain Tumor Classification. - Abdullah A. Asiri; Bilal Khan 003; Fazal Muhammad; Shams ur Rahman; Hassan A Alshamrani; Khalaf Alshamrani; Muhammad Irfan 008; Samar M. Alqhtani (Intell. Autom. Soft Comput., 2023)

Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks. - Muhammad Fawad; Muhammad Zahid Khan; Khalil Ullah; Hisham Alasmary; Danish Shehzad; Bilal Khan 003 (Sensors, 2023)

FEPP: Advancing Software Risk Prediction in Requirements Engineering Through Innovative Rule Extraction and Multi-Class Integration. - Muhammad Binsawad; Bilal Khan 003 (IEEE Access, 2024)

Advanced Detection of Abnormal ECG Patterns Using an Optimized LADTree Model with Enhanced Predictive Feature: Potential Application in CKD. - Muhammad Binsawad; Bilal Khan 003 (Algorithms, 2024)

Next-Generation Text Summarization: A T5-LSTM FusionNet Hybrid Approach for Psychological Data. - Bilal Khan 003; Muhammad Usman 011; Inayat Khan; Jawad Khan; Dildar Hussain; Yeong Hyeon Gu (IEEE Access, 2025)