PHC Global

Precision Health Consultants (PHC Global) is a Pakistani health care consultancy firm that leverages advances in genomics, data science, and digital technology to personalise health care and improve health outcomes.

They provide services in health care policy and strategy development, data analytics and informatics, and clinical research and trials. By working with government agencies, academic institutions, and private sector organizations, PHC Global is contributing to the development of a more effective, efficient, and equitable health system in Pakistan and beyond..

Official website: https://phcglobal.org

AI4GH project

AI-Sarosh is a knowledge hub for the responsible use of Artificial Intelligence for Sexual, Reproductive, and Maternal Health in South Asia.

The goal is to catalyze responsible AI innovations to improve SRMH outcomes by organizing and directing the efforts of specialty companies, academic institutions, research organizations, and IT firms.

Objectives:

1. Create a knowledge hub for the use of AI for SRMH in South Asia.
2. Identify opportunities to improve SRMH outcomes in the region.
3. Award and manage projects using AI innovations to address key challenges in SRMH.
4. Promote knowledge sharing on the use of AI for SRMH.
5. Catalyze a multi-disciplinary approach to solving key issues in SRMH through AI technologies.

Events

Dr. Muhammad Imran Khan

Project lead - Executive Director, PHC Global. Dr. Imran Khan is the founding executive director at PHC Global. His career spans more than two decades of research, implementation, and advocacy for improved coverage and the introduction of effective public health interventions in developing countries. Dr. Khan's specialized interest lies in evidence-based advocacy for efficient and equitable health systems delivery. As Lead for AI-Sarosh, Dr. Khan oversees the formulation and implementation of the AI for Health Global, South Asia vision and mission, and achiveing the over arching goals of innovation and sustainbility.

Mr. Deepak Bajracharya

Project Co-Lead. Executive Director of GTA Foundation, coordinating international research in Nepal. With extensive experience in healthcare and community settings, he has implemented antimicrobial stewardship and vaccination campaigns. Deepak has been a leader in sexual, reproductive, and maternal health initiatives, promoting family planning, women's education, and HIV/AIDS prevention. He has contributed as an editor and directed a documentary on reproductive health and women's empowerment. As Co-Lead for AI-Sarosh, Mr. Bajracharya oversight the logistical and technical part of the project from GTA, communicate the progress with the PHC Global team, facilitate the advocacy with the government and stakeholders, participate in the meetings and provide inputs, review of the RFP, monitoring of the activities and provide supportive guidance, and participate in the meeting with IDRC and stakeholders.

Dr. Noor Sabah

SRMH Expert. An accomplished researcher on maternal and child health. Her work focuses on health systems strengthening, governance & leadership. Her approach to systems improvements is through developing structures and processes to improve the supply of quality public services and introduce innovations to create demand for health services among communities, especially the underserved and marginalized populations. As the SRMH (sexual, reproductive, and maternal health) lead, Dr. Rakhshani oversees the AI-Sarosh processes and outputs through technical oversight and adoption of innovative solutions. She also serves as the gender and inclusion lead.

Mr. Kamran Aslam

Digital Health Expert. director of digital technologies and data analytics with an MS in Data systems degree from the University of Sheffield, England. He has over a decade of experience in progressively responsible roles within the tech industry. He has provided policy consultations for digital systems, requirement analysis for digital systems, system design analysis, and advanced data analysis. As digital health specilist he has successfully led the redesigning of the Pakistan health information system, Pakistan health knowledge hub, the national digital health strategy and framework for the Ministry of National health services, Regulations & Coordination, Govt. of Pakistan. He will be the lead of PMT and a member of technical advisory team. His responsibilities will include management of all activities of the project including formation of technical advisory team, development of calls for proposals, review of the submitted applications, and assess the progress of the awarded projects. Being the AI expert, he will assess the appropriateness and feasibility of the RFPs and proposals.

Dr. Bhim Singh Tinkari

Health systems expert. Has more than three decades of experience in the government system and WHO. He was a chief specialist (equivalent to secretary) in the Ministry of Health and Population. He has led the Family Welfare Division during the pandemic situation and introduced the COVID-19 vaccine and applied for the TCV vaccine to GAVI. Dr. Tinkari has experience leading the family planning, reproductive health, and maternal and child health programs of the Government of Nepal. He also led the National TB Center and Management Division. As a Health System Expert, Dr. TInkari will support in RFP development, support in assessing the RFPs, proposals and awarded projects on the health systems level integration and effects, support in advocacy with governments, guidance on organizing meetings, and dissemination, support in monitoring of the grantees and review reports.

Mr. Shah Haroon

Tech lead, Manager DTDA. Shah Haroon holds the position of IT Manager within PHC Global's Digital Technologies and Data Analytics department. His professional endeavors encompass the ideation, development and management of digital solutions across various sectors, including health, education, and human resources. He is driven by a keen interest in leveraging his technical expertise for projects that underpin meaningful, systemic change within service delivery institutions. As Tech Manager for the AI-SAROSH project, Shah Haroon contributes to the initiative's technical strategic vision. He is responsible for developing key digital mechanisms to ensure seamless alignment with the project's overarching objectives. A crucial part of his role involves devising robust mechanisms for effective data capture, with a focus on leveraging it to fuel further project enhancements.

AGA KHAN University

The project aims to conduct a longitudinal study to address perinatal depression in Pakistan, a critical concern with lasting effects on mothers and children. Using AI and machine learning like logistic regression, decision trees, and neural networks our goal is to create a predictive model for early-stage postpartum depression detection, improving support for pregnant and postpartum women, especially with the likely likelihood of risk factors. Through a 20-month study with surveys at multiple time points, the project is comprehensively exploring factors contributing to postpartum depression severity. The project advances perinatal depression understanding, benefiting women's well-being in Pakistan. It could also help reduce mental health stigma and requires ethical considerations, data privacy, and participant well-being focus.

More information find it here.

CMED Health Ltd

The project aims to address adolescent Sexual, Reproductive, and mental Health (ASRMH) challenges in Bangladesh by overcoming societal taboos and limited access to information and care. The solution involves an open-source AI engine integrated into the existing digital healthcare platform "SuSastho", providing health education, screening, doctor consultation, referral, and data analytics through a chatbot, referral engine, and stakeholder dashboard. Partnering with UNICEF and government entities, the project plans to conduct beta testing, seek clinical validations, and ensure cultural appropriateness through consultative workshops.

More information find it here.

Eminence Associates for Social Development

The project aims to develop an AI-based tool to detect perinatal depression with reduced screening time and improved accuracy. Our approach involves collecting high-quality eye fixation data and comparing it with existing eye fixation models to identify perinatal depression. The developed AI models' accuracy, sensitivity, specificity, and other relevant metrics will be assessed and compared to the depression scale and clinical diagnosis. The model would enable healthcare providers to detect and treat perinatal depression in women.

More information find it here.

mPower Social Enterprises Ltd

This project entails the development of a Machine-learning-based platform, that will take inputs from multiple sources of datasets, such as from MoH, public health NGOs, and private healthcare facilities for predicting the possibility of risk levels in pregnancies. During the project, we will undertake R&D to develop the platform, with an objective to reach an acceptable level of accuracy, and pilot in selected locations to document lessons learned from field-level execution.

More information find it here.

NAAMI

This project will do research, development, and pilot evaluation of an AI-assisted fetal ultrasound scanning system for community health nurses. AI models to automatically detect key fetal anatomical views and abnormalities during scanning will be trained by utilizing existing public datasets and newly collected data from two hospitals in Nepal: a teaching hospital in an urban center and a community hospital in a remote area. The project’s results will provide valuable framework and learnings for building reliable fetal ultrasound services at scale in rural and community health centers in LMIC settings.

More information find it here.

National University of Sciences and Technology

The AI predictive tool for gestational diabetes is an innovative, evidence-based solution for predicting diabetes risk in expectant mothers. It provides early detection and improves perinatal and postnatal outcomes. By integrating diverse clinical datasets and formulating effective algorithms using machine learning, we aim to create a tool for clinicians' daily use. A team of experts specialized in AI and software development from NUST, combined with the Shifa International Hospital's JCI-accredited clinical excellence guarantees the project's success.

More information find it here.

Faculty of Medicine, University of Colombo

A population-based Birth Cohort Study will be conducted in the Western Province of Sri Lanka with a Maternal Health Enhancement (MHE) mobile application. The app includes AI predictive models capable of predicting preterm birth, low birth weight, preeclampsia, perinatal mortality, and postpartum depression in advance. MHE will deliver health advice/alerts directly to the pregnant mother's mobile phone through push notifications with simultaneous alerts for healthcare providers. AI models will also be used in data analysis.

More information find it here.

Wiseyak

The project strives to address the high incidence of cervical cancer in low- and middle-income countries (LMICs). The key aim of the project is to provide an integrated system for integrating AI-driven colposcopy image diagnosis, remote consultation, and EMR system into a single platform to aid the doctor in delivering accurate and efficient patient care. The system will support the doctor by providing a paperless digital health platform upon which data analytics can be performed and success rates of interventions can be accurately measured. A secondary aim of the project is to develop/repurpose low-cost endoscopy and microscopy devices for AI-driven screening which can be scaled for use within remote healthcare sets.

More information find it here.