Regional Symposium on Innovation in science and technology

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Combining Machine Learning and Nanobiosensors for Improving Lung Cancer Detection

Authors :

Shakiba Nazemian¹ Soheil Sadr² Ashkan Hajjafari³ Khashayar Hajjafari⁴ Abbas Rahdar⁵ Mahdis Khajehmohammadi⁶ Hassan Borji⁷

1- Department of Pathobiology, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mas 2- Department of Pathobiology, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran 3- Department of Pathobiology, Faculty of Veterinary Specialized Science, Science, and Research Branch, Islamic Azad University, Tehran, Iran 4- Medical Doctor, Shahid Bahonar University of Kerman, Kerman, Iran 5- Department of Physics, University of Zabol, Zabol, Iran 6- Department of Basic Sciences, Faculty of Veterinary Medicine, Baft branch, Islamic Azad University, Baft, Iran 7- Department of Pathobiology, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran

Keywords :

Lung cancer،Nanotechnology،Nanobiosensors،Artificial intelligence

Abstract :

Abstract- Lung cancer is one of the most prevalent types of cancer in the world, and its clinical prognosis and early detection are of great importance. With recent advances in artificial intelligence and nanotechnology, combining machine learning (ML) and nanobiosensors has been considered a novel approach for diagnosing and monitoring lung cancer. Hence, the current review aims to examine the combination of these two technologies for lung cancer diagnosis and explores its potential and challenges. ML can identify patterns associated with lung cancer with its capabilities in processing complex data and simulating predictive models. Nanobiosensors, on the other hand, can detect biological changes at the molecular and cellular levels with high sensitivity. These two technologies allow for more accurate, faster, and non-invasive lung cancer diagnosis. In addition, using these two technologies simultaneously could help identify more advanced changes in the disease, even before clinical symptoms become apparent. In conclusion, combining machine learning and nanobiosensors offers a novel and efficient approach to lung cancer diagnosis that can significantly increase the accuracy of diagnosis and prognosis.

Papers List

List of archived papers

A novel therapy for treating hydatid cysts using nanoliposomal albendazole and mebendazole

Narges Lotalizadeh - Soheil Sadr - Ashkan Hajjafari - Nooshinmehr Soleymani - Hassan Borji

Classification of Non-Alcoholic Fatty Liver Disease Using Ultrasound Imaging and Deep Texture Representation

ALI FAROOGHI

تولید و توسعه نرم‌افزار شبیه‌ساز آموزش اپراتور واحد شیرین‌سازی گاز طبیعی

امید صباغ - میثم وحیدی فردوسی - محمدعلی فنایی شیخ الاسلامی

Effect of Smart Water Meters (SWM)' Installation on Water Table Fluctuations in the Roshtkhar Plain

Hossein Mohammadzadeh - Mahdi Torshizi

Mineralogy of atmospheric dust and potential risk of silicosis in residents of Saleh-Abad region (NE-Iran)

Amineh Darrudi - Mohamad Hosein Mahmudy Gharaie - Masumeh Taheri - Masood Minaee

The feasibility of automated gemstones identification using optical properties and Artificial Intelligence (AI)

Morteza Razmara

Application of Lasers in Precision Volume Measurement of Liquids

Ayda Sarkaki - Mohammad Reza Rashidian Vaziri - Seyed Mohammad Ali Abadi - Hadi Rastegar Mogahddam Rezaion - Mina Mayeli

تحدید جرعة کبریتات الألمنیوم المائیة اللازمة لإزالةCOD  والمعادن الثقیلة من میاه نهر قویق عند مصب الدباغات تبعا لترکیز المیاه الخام

میس الورده

Tuning surface structure of BiOI photocatalysts using magnetized methanol: Applied magnetic field

Sara Abolhasani - Ali Ahmadpour - Mostafa Gholizadeh

Combining Machine Learning and Nanobiosensors for Improving Lung Cancer Detection

Shakiba Nazemian - Soheil Sadr - Ashkan Hajjafari - Khashayar Hajjafari - Abbas Rahdar - Mahdis Khajehmohammadi - Hassan Borji