App/Software

Hugo Morales of Munai Health in Brazil will integrate OpenAI's ChatGPT-4 and other Large Language Models (LLMs) with Munai's Clinical Intelligence platform to help frontline healthcare providers adhere to guidelines for antimicrobial therapy and reduce antimicrobial resistance. Antibiotic-resistant bacteria cause over 20% of infections in Brazil. However, the antimicrobial stewardship programs designed to address this consist of complex protocols and there is little training for health workers in low-resource settings.

Shashi Jain of the Indian Institute of Science in India in collaboration with Uma Urs from Oxford Brookes University in the United Kingdom along with colleagues from Akaike and Kotak Mahindra Bank also in India, will build a GPT-enabled AI bot called SATHI, which stands for Scheme, Access, Training, Help, and Inclusion, to deliver information on the latest government financial schemes that support sectors, like micro-enterprises and farms, to potential customers and providers in rural and suburban India.

Praveen Devarsetty of the George Institute for Global Health in India will integrate an LLM into their SMARThealth Pregnancy application to enable two-way communication support for frontline health workers to improve healthcare services for pregnant and postpartum women in India. Reducing maternal and newborn mortality and morbidity is a global priority, particularly in low- and middle-income countries where information about medical conditions and pregnancy symptoms is difficult to access in simple terms and local languages.

Neal Lesh of Dimagi South Africa (Pty) Ltd. in South Africa will create an LLM-powered coach tailored to frontline workers that offers training, performance feedback, and encouragement to support their health and improve their productivity. Frontline programs serve billions of people; however, they rely on a hard-working, often overburdened workforce that receives limited support, particularly in low- and middle-income countries. They will work with 10–20 community health volunteers in Malawi to co-design three variations of the LLM-powered coach using their rapid LLM-building platform.

Theofrida Maginga of the Sokoine University of Agriculture in Tanzania will develop a ChatGPT-powered Swahili chatbot for smallholder farmers with limited literacy and scarce resources in Tanzania to detect crop diseases quickly and easily. Maize is one of the most important crops in Tanzania and generates up to 50% of rural cash income. Several diseases that afflict maize are hard to detect visually, leading to substantial losses in crop productivity and income.

João Paulo Souza of the Fundação de Apoio ao Ensino, Pesquisa e Assistência in Brazil will determine whether Large Language Models (LLMs) can be utilized as accurate information sources to guide healthcare provider decision-making. Frontline health workers must make real-life care decisions by distinguishing between relevant and irrelevant information and contextualizing it to their setting. This is particularly challenging in remote areas with limited healthcare specialists.

Amrita Mahale of ARMMAN in India, in collaboration with colleagues at ARTPARK also in India, will integrate an LLM-powered co-pilot into an existing learning and support application to improve the training of auxiliary nurses and midwives in India so they can better manage high-risk pregnancies. One woman dies in childbirth every twenty minutes in India. Many maternal and infant deaths could be prevented by improving access to critical care information and ensuring that health workers can detect risk factors and treat complications early on.

Nirat Bhatnagar of the Belongg Community Ventures Private Ltd. in India, in collaboration with colleagues at ARTPARK also in India, will develop a Large Language Model (LLM)-based tool to enable development practitioners, funders, and researchers to adopt more equitable approaches, particularly addressing the intersections of marginalization. They will assemble a comprehensive and trusted corpus of development research papers, reports, and media articles and use it to build a user-friendly website and a backend ChatGPT 4.0 API-based LLM model.

Firat Guder and Tony Cass of Imperial College London in the United Kingdom along with George Mahuku and James Legg at the International Institute of Tropical Agriculture in Tanzania are developing a low-cost, disposable electrochemical lateral flow assay for smartphones to rapidly detect crop viruses in the field and enable broad crop disease surveillance in low-income regions. Most diagnostic tests are laboratory-based, expensive, and slow.

M-mama improves access to emergency transportation to health facilities in rural areas comprising 1) a digital triaging and dispatch platform with a 24/7 toll-free dispatch center; 2) reliable emergency transport leveraging existing government owned ambulance fleets and vetted community drivers; 3) reliable and high-quality care at receiving facilities