Google Health has collaborated with Apollo Radiology International in India to leverage the former’s AI capabilities to improve early disease detection, especially for tuberculosis (TB), lung cancer, and breast cancer. 

TB is a major health concern in South Asia and Sub-Saharan Africa, and it lacks adequate radiologist interpretation for chest X-ray screenings, leading to delays in treatment and fatal outcomes. So, AI will help interpret these scans for TB signs, addressing the shortage of trained radiologists and inaccessible diagnostic tests in rural areas.

Similarly, lung cancer and breast cancer screenings in India face challenges due to limited expertise and accessibility. AI assists in making screenings more accessible and identifying incidental nodules, potentially improving early detection rates. With breast cancer having a high mortality rate in India and a scarcity of trained radiologists for interpretation, AI offers hope for scaling up mammogram screenings.

Looking ahead, the partnership seeks to expand AI-powered screening initiatives, with Apollo Radiology International aiming to provide three million free screenings over the next decade. The partnership is an effort to democratise access to healthcare services and improve health outcomes for communities across India.

In addition to early disease detection, Google.org supports initiatives like ARMMAN’s mMitra that address maternal and child health challenges. By harnessing AI predictions to deliver targeted preventive care messages via mobile services, mMitra aims to empower new and expectant mothers with essential health information, ultimately contributing to improved health outcomes for mothers and children in India.

Google is clearly all about making an impact and has a greater affinity for life science and healthcare. Recently, Google Research launched a new medical chatbot called AMIE, specialising in expert-level differential diagnosis.

Unlike the big tech’s previous AI model, Med-PaLM 2, which focuses on medical summaries or answering questions, AMIE serves as a diagnostic tool, generating differential diagnoses. AMIE is built on Google’s PaLM and trained on datasets containing medical conclusions, summaries, and actual clinical conversations.