HEC · NCBC · SZABIST University

Predictive Analytics
for Smart Healthcare

Transforming healthcare across Sindh through the power of data and artificial intelligence — predicting risks, protecting lives, and empowering decisions.

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11/130
Proposals Selected
99%
TB Detection Accuracy
23+
Team Members
AI Prediction Engine
Live
Peak Model Accuracy
99% across 4 AI prediction modules
IMR 87% MMR 90% LHW 78% TB 99%
About Us

Turning Data Into Health Impact

The Predictive Analytics (PA) Lab was established at SZABIST under the National Center for Big Data and Cloud Computing (NCBC). Selected through a highly competitive process — 11 out of 130 nationwide proposals — the lab is dedicated to improving public health outcomes across Sindh through AI and data science.

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Healthcare data and AI in action
Our Mission

From District Data to District-Saving Decisions

Every signal our systems catch — a missed vaccination, a maternal risk, a TB case — becomes an early warning that reaches health workers before it becomes a crisis.

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Everything We're Building

15Centers & Labs
Research Centers & Labs

4 national centers and 11 affiliated labs nationwide, spanning AI, robotics, cyber security and cloud computing.

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5Active Programs
Health Programs

Five active programs covering immunization, nutrition, maternal health, TB control, and lady health workers.

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24/7Live Monitoring
DHAS & DHPS Systems

Our core district health analytics and prediction platforms, turning raw health data into early warning signals.

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4Prediction Modules
AI Prediction Systems

Four modules predicting infant and maternal mortality risk, LHW performance, and clinical outcomes.

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99%Detection Accuracy
TB AI — TBXNet

Globally recognized AI models for faster, more accurate tuberculosis diagnosis, deployed in the field today.

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13+Publications & Apps
Publications & Apps

13+ peer-reviewed publications and mobile applications putting our research directly into practitioners' hands.

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Our People

The Team Behind the Predictions

A multidisciplinary group of researchers, analysts, and engineers turning health data into decisions that reach the field.

Prof. Dr. Muhammad Usman

Principal Investigator
Jul 2018 – Present

Dr. Muhammad Imran

Co-Principal Investigator
Jul 2024 – Present

Dr. Muhammad Usman (Awan)

Team Lead
Jan 2025 – Present
Meet the full 23+ member team
Research Impact

Published, Peer-Reviewed, Field-Tested

A sample of our 13+ publications spanning machine learning, deep learning, and AI-driven public health research.

Deep learning framework for TB detection from chest X-ray images — Tuberculosis, 2022
Public health management for maternal mortality reduction in smart cities — IEEE Engineering Management Review, 2024
Encoder-decoder via vision transformer for colorectal polyp segmentation — Engineering Applications of AI, 2024
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Recognition

Nationally & Globally Recognized

Four milestones that mark our work moving from research into real-world impact.

HEC National Recognition 2025

Recognized by Higher Education Commission of Pakistan for contributions to AI and healthcare innovation.

Stop TB Partnership — Global Recognition

TBXNet++ globally recognized by the Stop TB Platform hosted by UNOPS for innovation and impact.

Government of Sindh Health Department

AI healthcare solutions presented to senior leadership, chaired by Dr. Azra Fazal Pechuho, Minister for Health.

DOPASI Foundation — First Commercial Sale

First commercial deployment of TBXNet++ for community-based TB screening in underserved communities.

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Let's Build the Healthier Tomorrow — Together

Interested in collaborating, partnering, or learning more about our work? We'd love to hear from you.

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