Department of Science & Humanities Research Groups

EHDS (Environment, and Health Data Science) Lab was established by Prof. Dr. Saman Shahid in 2020. The research lab is committed to solving issues of digital health care through artificial intelligent models and handling monitoring of environment’s data received for simulation & modeling. The focus of data science and models in health is to revolutionize healthcare by harnessing the power of artificial intelligence to improve patient outcomes, enhance diagnostics, optimize treatments, and advance medical research. AI models are developed and deployed with the goal of transforming healthcare delivery and addressing the complex challenges faced by the healthcare industry.

Data science plays a crucial role in addressing environmental hazards and promoting sustainability. By harnessing the power of data analysis, modeling, and predictive analytics, data science can contribute to understanding, mitigating, and managing environmental risks.

The Environment and Health Data Science Laboratory’s mission is to apply data science and sophisticated analytical approaches to key challenges at the confluence of the environment and human health. Our major purpose is to provide practical insights and evidence-based solutions that help to identify, mitigate, and avoid ecological hazards and their effects on human well-being.

We strive to contribute to the development of evidence-based policies, interventions, and strategies that promote sustainable environments and safeguard human health for present and future generations. Through simulations and modeling, artificial intelligence, statistical analyses, bioinformatics, sensors, specialized software, and engineering designs, the laboratory aims to study, report, analyze, develop, predict, and promote health and safety resulting from natural or built environmental impacts. The team included research assistants, MS students, and faculty members. They have published around 20+ international articles and conferences.

Principal Investigator

Prof. Dr. Saman Shahid deals with the teaching of Physics to BS Computer Science, Data Science, and Electrical Engineering programs. Her doctoral research work was related to brain cancer genetics and the discovery of mutations induced by environmental radiation with bioinformatics tools.

She also teaches Environmental Sciences courses to MS/Ph.D. programs at the National University of Computer & Emerging Sciences, NUCES-FAST, and Lahore Campus. She has published 91 research articles in national & international journals. She has also published 40 abstracts at different national and international conferences. Her current impact factor is 118.1. She is also a peer reviewer and editorial board member of some local and international journals. Her areas of interest are Artificial Intelligence (AI) in Medicine & Environment, Medical/Health Physics, Medical Radiation Physics, Environmental Health, and Bioinformatics.

Collaborators

• Prof. Dr. Muhammad Anwar Chaudary (Punjab Institute of Neurosciences - PINS Lahore)
• Dr. Aatir Javaid (Assistant Professor, Department of Orthopedics, University of Lahore)
• Dr. Sadaf Iftikhar (Associate Professor, Department of Neurology, King Edward Medical University Lahore)
• Engr. Adnan Nadeem (Production unit, PEAB AB, Sweden)
• Engr. Usama Butt (Department of Civil and Environmental Engineering, Clarkson University, Potsdam, New York, USA.)
• Mr. Shahid Zikria (Department of Computer Science, ITU, Pakistan)
• Dr. Jawad Rasheed (Associate Professor, Department of Computer Engineering, Istanbul Sabahattin Zaim University, Istanbul, Turkey)
• Dr. Tunc Asuroglu (Associate Professor, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland)
• Prof. Dr. Kamran Hussain (Professor, Department of Neurosurgery, Central Park Teaching Hospital, Lahore Pakistan)
• Dr. Asma Majeed (Assistant Professor, Institute of Agro-Industry & Environment, Faculty of Agriculture & Environment, the Islamia University of Bahawalpur)

Goals and Domains

Key Mission Objectives

• Data-driven investigation: Conducting a rigorous scientific study on complex environmental and health datasets using cutting-edge data science approaches and technologies. We want to find patterns, connections, and trends that will help us make better decisions and comprehend the intricate interplay between the environment and human health.
• Collaborative Approach: Promoting interdisciplinary collaboration among professionals in environmental science, health science, data science, and other subjects. We attempt to form collaborative efforts with academic institutions, government agencies, and non-profit groups to address difficult environmental and health issues.
• Knowledge Translation: Translating research findings into actionable recommendations and policy implications to guide effective interventions and strategies. We aim to bridge the gap between scientific research and practical application by communicating our findings to policymakers, stakeholders, and the general public in an accessible and impactful manner.
• Capacity Building: Developing and sharing tools, methodologies, and best practices in data science applied to environment and health research. We aim to empower researchers, practitioners, and policymakers with the necessary skills and knowledge to harness the potential of data science for addressing environmental and health challenges.

Projects Completed

• Computational imaging for rapid detection of grade-I cerebral small vessel disease (cSVD)
• Digital Knee Osteoarthritis Diagnosis:
• Lifetime risk of radiation induced severe hereditary stochastic (SHS) effects in medical radiation personnel
• Prediction of Radiation-Induced Abnormality in Liver Enzymes from Machine Learning (ML) Algorithms.
• Assessment of Ammonia, Carbon Dioxide, and Carbon Monoxide from Real-Time Sensing Devices Due to Traffic Congestion

Projects in progress

Environmental issues

• Evaluation of Socioeconomic and Environmental Impacts of Barrages by Analytical Hierarchy Process (AHP)

• Volumetric properties of hot mix asphalt (HMA) using the Marshall mix design with tire crumb rubber (CR). Journal of Rubber Research (under review)

• Comparison Of Different Properties Of Old Era Bricks And New Era Bricks.

• Assessment of green roof sustainability

• Monitoring of ammonia, carbon dioxide, and carbon monoxide by traffic congestion

• Green concretes and impacts

• Climate change detection from remote satellite data and machine learning models

AI & Health

• Diagnosis of cerebral small vascular disease from machine learning

• Identification of venous stroke from MRV and CT scans from computational imaging

• Digital orthopedics: automated systems for knee osteoarthritis and fractures

• Assessment of surgical requirements in high grade glioma patients

• Rapid computer aided diagnosis system for brain tumors

• Epilepsy and seizure detection models

• Psychiatric Disorder Classification through EEG signals using Deep Learning

• Digital Orthopedics as a learning tool for young physicians.

Selected Publications

AI & Health

• S Shahid, Masood K, Khan AW. International Conference on Radiation Safety: Improving Radiation Protection. International Atomic Energy Agency (IAEA), Vienna, Austria. CN 279. Predicting liver transaminases alterations from low-dose medical radiation exposure through machine learning (ML) approach. November 9-20, 2020, PP. 200-201.

• Iftikhar S, Shahid S, Hassan MU, Ghias M. Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI). Pakistan Journal of Pharmaceutical Sciences. 2020 Sep 1;33(5):2399-404. (Impact Factor: 0.562).

• Shahid S, Masood K, Khan AW. Prediction of Impacts on Liver Enzymes from the Exposure of Low-Dose Medical Radiations through Artificial Intelligence (AI) Algorithms. Revista da Associação Médica Brasileira. 2021 Feb, 67(2); 248-259. (Impact factor: 1.209)

• S Shahid, S Iftikhar. Machine learning models to predict neuropsychiatric disorders in various brain tumors. 17 Feb 2022. Current Medical Research and Opinion, Taylor & Francis. (Impact factor: 2.705)

• S Shahid, A Javaid. Application of machine learning decision tree in diagnosing joint pain. ©2022 IEEE Turkey Section. TIPTEKNO’ 22 Medical Technology Congress. 31 Oct- 2 Nov, 2022. Indexed in IEEE Xplore. pp. 93-96

• Ahmed Z, Shahid S. Improving emotion detection through artificial intelligence from EEG brainwave signals. ©2022 IEEE Turkey Section. International Conference on Artificial Intelligence of Things (ICAIoT). 29-30, December 2022. Indexed in IEEE Xplore.

• S Shahid, MA Chaudary. Computational biomarkers for the decision of neurological treatment for brain tumors. Pakistan Journal Of Neurological Surgery. 2022 Vol. 26(4). P. xi-xii.

• Chaudary MA, Shahid S. Neurosurgery with Artificial Intelligence. Editorial Pakistan Journal Of Neurological Surgery. 2022;26(1).

Environmental Data Science:

• M Usman, S Shahid, S Ali, M Kaleem Ullah. Numerical Simulations of Turbulent and Flow Characteristics of Complex River Reach in Pakistan. Environmental Engineering Research. 2022;28(1): 210369. (Impact factor: 3.932)

• A Majeed, S Shahid, S Ali, N Firdous. Safety assessment of water purification plants of Lahore. Journal of the Pakistan Institute of Chemical Engineers. (HEC recognized and JCR listed) Vol. 50(2): 2023.

• Ghafoor H, Abbas S, Shahid S, Ali S. Investigating the potential of waste polyethylene in concrete. InProceedings of the Institution of Civil Engineers-Waste and Resource Management 2023 Mar 14 (pp. 1-8). Thomas Telford Ltd. Paper 2200028, 2023.

• Investigating the potential of waste plastic bags in concrete. WASTE MANAGEMENT & RESEARCH-ICE 2023 UK.

• S Shahid, Chaudary MA, Majeed A, Siddique RA. Mental disorders emerging from the climate change: A need to mitigate the eco-anxieties. FUUAST J Biol. 2021; June 11(1): 69-73.

• Shahid S, Aslam MA, Ali S, Zameer M, Faisal M. Self‐healing of cracks in concrete using Bacillus strains encapsulated in sodium alginate beads. ChemistrySelect. 2020 Jan 9;5(1):312-23. (impact factor: 1.716)

• Raham I, Shahid Saman, Ali S. High Strength Green (HSG) Concrete with Coal Fly Ash. Revista Ingeniería de Construcción. 2023 Apr 1;38(1).