CERVEX enables auto- mated analysis of cervical cytology microscope fields by linking cell classification, computation-linked spatial evidence, and in- terpretable numerical morphology indices in one pipeline.
Background Cervical cancer remains a leading cause of cancer death among women in sub-Saharan Africa, with Tanzania bearing a disproportionate burden. The critical shortage of trained pathologists, coupled with the unprecedented disease burden in low-resource settings, underscores the urgent need for point-of-care scre...
S. Sang'udi, David Muhunzi, W. Frank et al.· Frontiers in Digital Health· 0 citations
AI-assisted analysis of Pap smear images represents a promising approach for supporting early cervical cancer detection and improving cervical screening workflows and should focus on large and diverse datasets, standardized evaluation protocols, explainable AI, external clinical validation, and integration of AI system...
Nandita Mahesh· Advanced International Journ...· 0 citations
Cervical cancer is highly preventable when precancerous cytological abnormalities are identified early; however, manual Pap smear assessment remains labour-intensive, time-consuming, and prone to inter-observer variability. Automated cervical cytology is also challenging because Pap smear cell images often exhibit subt...
J. V. Panicker, G. Gopakumar, J. J. Nair· Discover Artificial Intellig...· 0 citations
Examining thyroid fine needle aspiration (FNA) can grade cancer risks, derive prognostic information, and guide follow-up care or surgery decision-making. However, thyroid cytology’s diagnostic cues are more dispersed compared with pathology images in other disciplines, making standard annotation strategy for AI diagno...
Jun-Chao Zhu, Yiqing Shen, Rui-Fei Du et al.· IEEE Transactions on Image P...· 0 citations
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
MIT News · Artificial Intelligence· news.mit.eduOct 30, 2026
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
