Artificial intelligence in lung cancer imaging: unfolding the future

M Cellina, M Cè, G Irmici, V Ascenti, N Khenkina… - Diagnostics, 2022 - mdpi.com
Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays
an essential role in each phase of lung cancer management, from detection to assessment …

A review of deep learning techniques for lung cancer screening and diagnosis based on CT images

MA Thanoon, MA Zulkifley, MAA Mohd Zainuri… - Diagnostics, 2023 - mdpi.com
One of the most common and deadly diseases in the world is lung cancer. Only early
identification of lung cancer can increase a patient's probability of survival. A frequently used …

Artificial intelligence in lung cancer screening: the future is now

M Cellina, LM Cacioppa, M Cè, V Chiarpenello… - Cancers, 2023 - mdpi.com
Simple Summary Lung cancer is a widespread malignant tumour with a high mortality and
morbidity rate and is frequently diagnosed in the middle and late stages when few therapies …

Application and performance of artificial intelligence technology in detection, diagnosis and prediction of dental caries (DC)—a systematic review

SB Khanagar, K Alfouzan, M Awawdeh, L Alkadi… - Diagnostics, 2022 - mdpi.com
Evolution in the fields of science and technology has led to the development of newer
applications based on Artificial Intelligence (AI) technology that have been widely used in …

A survey on artificial intelligence in pulmonary imaging

PK Saha, SA Nadeem… - … Reviews: Data Mining …, 2023 - Wiley Online Library
Over the last decade, deep learning (DL) has contributed to a paradigm shift in computer
vision and image recognition creating widespread opportunities of using artificial …

Machine learning empowering personalized medicine: A comprehensive review of medical image analysis methods

I Galić, M Habijan, H Leventić, K Romić - Electronics, 2023 - mdpi.com
Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …

[HTML][HTML] An improved SqueezeNet model for the diagnosis of lung cancer in CT scans

M Tsivgoulis, T Papastergiou… - Machine Learning with …, 2022 - Elsevier
Lung cancer is the leading cause of cancer deaths nowadays and its early detection and
treatment plays an important role in survival of patients. The main challenge is to acquire an …

The effects of artificial intelligence assistance on the radiologists' assessment of lung nodules on CT scans: a systematic review

LJS Ewals, K van der Wulp… - Journal of clinical …, 2023 - mdpi.com
To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists,
many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are …

[HTML][HTML] Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis

YEI El-Bouzaidi, O Abdoun - Scientific African, 2023 - Elsevier
In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China,
quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective …

YOLOv4-based CNN model versus nested contours algorithm in the suspicious lesion detection on the mammography image: A direct comparison in the real clinical …

A Kolchev, D Pasynkov, I Egoshin, I Kliouchkin… - Journal of …, 2022 - mdpi.com
Background: We directly compared the mammography image processing results obtained
with the help of the YOLOv4 convolutional neural network (CNN) model versus those …