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Organization Contact Information | |
| Name: | Predictive Analytics Lab - SZABIST University |
| Street 1: | Plot # 67, Street No. 9, H-8/4, Islamabad |
| Street 2: | |
| City: | Islamabad |
| Province: | Federal Capital Territory |
| Post Code: | 46000 |
| Country: | Pakistan |
| Phone: | 009251 – 4863363-65 Ext 204 |
| Organization Email: | ilm@szabist-isb.edu.pk |
| Web Site: | http://www.szabist-isb.edu.pk/ |
| Other Online Presence: | www.predictive-lab.com |
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General Information | |
| Board Constituency: | None |
| Is your organization legally registered in your country: | Yes |
| If yes, please enter your registration number: | 3028484269 |
| Organization Type - Primary: | Academic / Research Institution |
| Organization Type - Secondary: | None |
| Organization Description: | |
| 1. Mission and Main Focus of Work: Predictive Analytics Lab, part of Pakistan’s National Center of Big Data and Cloud Computing, focuses on leveraging Artificial Intelligence (AI) and Machine Learning (ML) for healthcare solutions. Our mission is to develop AI-driven diagnostic tools that enhance early disease detection and improve patient outcomes. We specialize in Computer-Aided Diagnosis (CAD) systems, predictive modeling, and decision support tools for various public health challenges. 2. Interest in Tuberculosis (TB): Tuberculosis remains a significant public health concern in Pakistan, with a high disease burden and diagnostic challenges, particularly in resource-limited areas. Early and accurate detection of TB is crucial for effective treatment and containment. Our interest in TB stems from the urgent need for innovative, AI-based solutions to support timely and efficient diagnosis, ultimately aiding in Pakistan’s goal of TB eradication. 3. Current and Planned Efforts for TB Control: We are actively developing an AI-powered CAD tool for TB detection using chest X-rays. This system employs Deep Learning models trained on large-scale datasets to assist radiologists in identifying TB-related abnormalities with high accuracy. Our goal is to integrate this tool into healthcare settings across Pakistan, particularly in rural and underprivileged regions where access to expert radiologists is limited. Additionally, we plan to collaborate with public health authorities, NGOs, and research institutions to enhance TB screening, facilitate early detection, and contribute to Pakistan’s efforts in eliminating TB. |
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| Do you know about the UNHLM declaration: | Yes |
Specializations / Areas of Work | |
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Delivery of health services and care Funding, including innovative and optimized approach to funding TB Care Research and Development Technical Assistance Working on Key Populations related to TB |
Other Organization Information | |
| Total number of staff in your organization: | 100 + |
| Number of full-time staff who are directly involved with TB: | 11 - 25 |
| Number of part-time staff who are directly involved with TB: | 6 - 10 |
| Number of volunteers who are directly involved with TB: | 6 - 10 |
| How did you hear about the Stop TB Partnership: | World TB Day |
| If you were informed or referred by another partner of the Stop TB Partnership please tell us who: | |
| Why do you wish join the Stop TB Partnership: | Involvement in Stop TB Working Groups |
| Are you a member of a Stop TB national partnership: | Pakistan |
| Are you in contact with your national TB programme: | Yes |
| Please tell us how your organization is contributing to your country's national TB control plan: | |
| Predictive Analytics Lab is committed to supporting Pakistan’s National TB Control Program (NTP) by integrating Artificial Intelligence (AI) into TB detection and diagnosis. Our AI-powered Computer-Aided Diagnosis (CAD) tool for TB detection using chest X-rays aligns with the NTP’s objectives of early diagnosis, improved accessibility, and enhanced disease surveillance. Our contributions include: 1. Early and Accurate TB Detection – Our AI model assists radiologists in identifying TB-related abnormalities with high precision, reducing diagnostic delays and enabling timely treatment. 2. Expanding Screening Capacity – By deploying AI-based TB screening in healthcare facilities, especially in remote and underserved areas, we enhance access to quality diagnostic tools. 3. Reducing Diagnostic Burden – Our tool aids overburdened healthcare professionals by providing rapid, automated TB screening, ensuring efficiency in patient management. 4. Research and Collaboration – We actively engage with health authorities, researchers, and NGOs to refine AI models, ensuring continuous improvement and effective implementation in Pakistan’s TB control strategy. Through these efforts, we contribute to Pakistan’s goal of reducing TB prevalence and moving towards eradication by leveraging AI for smarter, faster, and more accessible TB diagnosis. |
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Geographical Reach | |
| Which country is your headquarters located in: | Pakistan |
| Which countries do you do operate in: (This includes countries you are conducting activities in) |
Pakistan |
Contribution | |
| Please tell us how your organization will contribute to the Global Plan to Stop TB by briefly describing its involvement in any of the areas of work listed below: | |
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New Diagnostics: Contribution of Predictive Analytics Lab to the Global Plan to Stop TB Predictive Analytics Lab is dedicated to leveraging Artificial Intelligence (AI) to support the Global Plan to Stop TB (2023-2030) by enhancing TB diagnosis and facilitating early detection. Our contributions align with key focus areas of the plan, particularly in Innovations in TB Diagnosis, Universal Health Coverage (UHC) & Primary Healthcare, and Ending TB in High-Burden Countries. 1. Innovations in TB Diagnosis AI-Based TB Detection (2024-Present, Pakistan): We have developed an AI-powered Computer-Aided Diagnosis (CAD) tool for TB detection using chest X-rays, enabling faster and more accurate screening. Scalability and Deployment (2025-Onward, Pakistan & Potential Global Collaboration): We plan to collaborate with government health agencies and global health organizations to integrate our AI model into national TB screening programs, particularly in resource-limited settings. 2. Universal Health Coverage (UHC) & Primary Healthcare Enhanced Accessibility (2024-Present, Pakistan): Our AI-based solution helps bridge the gap in diagnostic services, especially in rural and underserved areas where expert radiologists are unavailable. Collaboration with Public Health Systems (2025-Onward, Pakistan): We aim to integrate our tool with Pakistan’s National TB Control Program (NTP) and explore partnerships with regional health bodies for broader adoption. 3. Ending TB in High-Burden Countries Pakistan-Specific Impact (2024-2030, Pakistan): Pakistan is among the high TB-burden countries, and our AI tool contributes directly to early case detection and improved treatment initiation, reducing transmission rates. Global Collaboration (2026-Onward, Other High-Burden Regions): We plan to expand our AI-based TB diagnostic tool to other high-burden regions through partnerships with international TB control organizations and research institutions. By integrating AI into TB screening, Predictive Analytics Lab is committed to accelerating progress toward the Global Plan to Stop TB, ensuring faster diagnoses, broader screening coverage, and strengthened healthcare infrastructure in Pakistan and beyond. Fundamental Research: Our accuracy and research work is already published internationally, Please see the below link for your reference [https://www.predictive-lab.com/publications.html] |
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Declaration | |
| Declaration of interests: No conflicts of interest were delacred. | |
| Application date: | June 6, 2023 |
| Last updated: | April 3, 2025 |