Abstract: Methods and systems for automated assessment of respiratory cytology specimens. Embodiments disclosed herein relate to oncology, and more particularly to automated assessment of respiratory cytology specimens for adequacy, diagnosis and treatment decisions for lung carcinoma. A method disclosed herein includes predicting an adequacy of the respiratory cytology specimens using Artificial Intelligence (AI)/deep learning models. The method further includes diagnosing and staging the respiratory cytology specimens on predicting that the respiratory cytology specimens are adequate for further processing. The method further includes generating at least one of an adequate report, an inadequate report, and a diagnosis and staging report.