An Iris based Lungs Pre-diagnostic System

Tassadaq Hussain (1) , Amna Haider (1) , Abdul Malik Muhammad (1) , Areeb Agha (1) , Bilal Khan (1) , Fawad Rashid (1) , Muhammad Saad Raza (1) , Moainud Din (1) , Mehran Khan (1) , Sami Ullah (1) , Abdelmalik Taleb-Ahmed (2) , Eduard Ayguadé

1 Riphah International University
2 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201

Human lungs are essential respiratory organs. Different Obstructive Lung Diseases (OLD) such as bronchitis, asthma, lungs cancer etc. affects the respiration. Diagnosing OLD in the initial stage is better than diagnosing and curing them later. The delay in diagnosing OLD is due to expensive diagnosing tool and experts requirement. Therefore, a non-invasive diagnosing tool for OLD is required that identifies dysfunctional lungs without the support of expert, complex and expensive diagnosing types of equipment. In this work, we design an Iris based Lungs Pre-diagnostic System (ILPS). The ILPS takes iris images as input and identifies dysfunctional Lungs based on iridology map. While testing with 50 lungs patients, the results confirm that the ILPS identifies dysfunctional lungs patients with the accuracy of 88%.

Mots clés: Artificial Intelligence; Embedded Computer Vision; Health-care; Iridology

Domaines: Sciences de l'ingénieur [physics]

Tassadaq Hussain, Amna Haider, Abdul Malik Muhammad, Areeb Agha, Bilal Khan, et al.. An Iris based Lungs Pre-diagnostic System. 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019, Jan 2019, Sukkur, Pakistan. pp.1-5, ⟨10.1109/ICOMET.2019.8673495⟩. ⟨hal-03676764⟩