A systematic review of modern approaches in healthcare systems for lung cancer detection and classification

SK Pandey, AK Bhandari - Archives of Computational Methods in …, 2023 - Springer
Lung cancer has become a prevalent form of cancer; it can be found in persons of all age
groups. The early stage identification of lung cancer is required to control the integrated …

Comprehensive review of reinforcement learning in lung cancer diagnosis and treatment: Taxonomy, challenges and recommendations

M Ghorbian, S Ghorbian - Computers in Biology and Medicine, 2024 - Elsevier
Lung cancer (LuC) is one of the leading causes of death in the world, and due to the
complex mechanisms and widespread metastasis, diagnosis and treatment are challenging …

[HTML][HTML] A modified convolutional neural network framework for categorizing lung cell histopathological image based on residual network

S Wadekar, DK Singh - Healthcare Analytics, 2023 - Elsevier
Computational technology has drastically improved the medical and Healthcare fields in the
last few years. Many new diagnostic techniques are introduced with the help of computer …

Improved Model for Genetic Algorithm-Based Accurate Lung Cancer Segmentation and Classification.

K Jagadeesh, A Rajendran - Computer Systems Science & …, 2023 - search.ebscohost.com
Lung Cancer is one of the hazardous diseases that have to be detected in earlier stages for
providing better treatment and clinical support to patients. For lung cancer diagnosis, the …

Lung cancer detection by using probabilistic majority voting and optimization techniques

KM Sünnetci, A Alkan - International Journal of Imaging …, 2022 - Wiley Online Library
The number of people dying from lung cancer in the world is increasing day by day.
Therefore, early diagnosis of lung cancer holds a prominent position for the recovery of …

FocalNeXt: A ConvNeXt augmented FocalNet architecture for lung cancer classification from CT-scan images

T Gulsoy, EB Kablan - Expert Systems with Applications, 2025 - Elsevier
Early and accurate diagnosis of lung cancer, a life-threatening disease, is critical to the
successful treatment of patients with the disease. On the other hand, it is well known that the …

Lung cancer detection using machine learning

S Bharathy, R Pavithra - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Lung disease is one of the most common disease that is affected in our early stage to
improve the rate of patients survival. For the radiologist the diagnosis of cancer is the most …

Analysis based on machine and deep learning techniques for the accurate detection of lung nodules from CT images

RV Kaulgud, A Patil - Biomedical Signal Processing and Control, 2023 - Elsevier
The imaging modality of computed tomography (CT) is significant for the diagnosis of lung
cancer. Doctors, surgeons, radiologists, and oncologists choose CT scanning to find these …

A systematic review on deep learning‐based automated cancer diagnosis models

R Tandon, S Agrawal, NPS Rathore… - Journal of Cellular …, 2024 - Wiley Online Library
Deep learning is gaining importance due to its wide range of applications. Many researchers
have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This …

A proposed methodology for detecting the malignant potential of pulmonary nodules in sarcoma using computed tomographic imaging and artificial intelligence-based …

E Baidya Kayal, S Ganguly, A Sasi, S Sharma… - Frontiers in …, 2023 - frontiersin.org
The presence of lung metastases in patients with primary malignancies is an important
criterion for treatment management and prognostication. Computed tomography (CT) of the …