[HTML][HTML] 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 …

PGC1α in the kidney

MR Lynch, MT Tran, SM Parikh - American Journal of …, 2018‏ - journals.physiology.org
Acute kidney injury (AKI) arising from diverse etiologies is characterized by mitochondrial
dysfunction. The peroxisome proliferator-activated receptor γ coactivator-1alpha (PGC1α), a …

AI-based smart prediction of clinical disease using random forest classifier and Naive Bayes

V Jackins, S Vimal, M Kaliappan, MY Lee - The Journal of …, 2021‏ - Springer
Healthcare practices include collecting all kinds of patient data which would help the doctor
correctly diagnose the health condition of the patient. These data could be simple symptoms …

[HTML][HTML] Machine-learning methods for computational science and engineering

M Frank, D Drikakis, V Charissis - Computation, 2020‏ - mdpi.com
The re-kindled fascination in machine learning (ML), observed over the last few decades,
has also percolated into natural sciences and engineering. ML algorithms are now used in …

[HTML][HTML] A sustainable IoHT based computationally intelligent healthcare monitoring system for lung cancer risk detection

S Mishra, HK Thakkar, PK Mallick, P Tiwari… - Sustainable Cities and …, 2021‏ - Elsevier
A sustainable healthcare focuses on enhancing and restoring public health parameters
thereby reducing gloomy impacts on social, economic and environmental elements of a …

[PDF][PDF] Advancements in early detection of lung cancer in public health: a comprehensive study utilizing machine learning algorithms and predictive models

MS Bhuiyan, IK Chowdhury, M Haider… - Journal of Computer …, 2024‏ - researchgate.net
Lung cancer stands as the leading cause of death in the United States, attributed to factors
such as the spontaneous growth of malignant tumors in the lungs that can metastasize to …

Detection of lung cancer in CT scans using grey wolf optimization algorithm and recurrent neural network

VK Gunjan, N Singh, F Shaik, S Roy - Health and Technology, 2022‏ - Springer
Purpose For radiologists, identifying and assessing thelung nodules of cancerous form from
CT scans is a difficult and laborious task. As a result, early lung growing prediction is …

[HTML][HTML] A survey of neural network-based cancer prediction models from microarray data

M Daoud, M Mayo - Artificial intelligence in medicine, 2019‏ - Elsevier
Neural networks are powerful tools used widely for building cancer prediction models from
microarray data. We review the most recently proposed models to highlight the roles of …

[Retracted] Lung Cancer Prediction from Text Datasets Using Machine Learning

C Anil Kumar, S Harish, P Ravi, M Svn… - BioMed Research …, 2022‏ - Wiley Online Library
Lung cancer is the major cause of cancer‐related death in this generation, and it is expected
to remain so for the foreseeable future. It is feasible to treat lung cancer if the symptoms of …

Physical laws meet machine intelligence: current developments and future directions

T Muther, AK Dahaghi, FI Syed, V Van Pham - Artificial Intelligence Review, 2023‏ - Springer
The advent of technology including big data has allowed machine learning technology to
strengthen its place in solving different science and engineering complex problems …