Advances in genomic data and biomarkers: revolutionizing NSCLC diagnosis and treatment
JC Restrepo, D Dueñas, Z Corredor, Y Liscano - Cancers, 2023 - mdpi.com
Simple Summary In the field of non-small cell lung cancer (NSCLC), there have been
significant advancements in genomic data and bioinformatics tools, which have improved …
significant advancements in genomic data and bioinformatics tools, which have improved …
Deep learning for lung cancer diagnosis, prognosis and prediction using histological and cytological images: a systematic review
Simple Summary Lung cancer is one of the most common and deadly malignancies
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
Optimization system based on convolutional neural network and internet of medical things for early diagnosis of lung cancer
Y Hussain Ali, V Sabu Chooralil, K Balasubramanian… - Bioengineering, 2023 - mdpi.com
Recently, deep learning and the Internet of Things (IoT) have been widely used in the
healthcare monitoring system for decision making. Disease prediction is one of the …
healthcare monitoring system for decision making. Disease prediction is one of the …
Exploring local explanation of practical industrial AI applications: A systematic literature review
In recent years, numerous explainable artificial intelligence (XAI) use cases have been
developed, to solve numerous real problems in industrial applications while maintaining the …
developed, to solve numerous real problems in industrial applications while maintaining the …
A wavelet neural operator based elastography for localization and quantification of tumors
Abstract Background and Objectives The application of intelligent imaging techniques and
deep learning in the field of computer-aided diagnosis and medical imaging have improved …
deep learning in the field of computer-aided diagnosis and medical imaging have improved …
A robust ensemble of convolutional neural networks for the detection of monkeypox disease from skin images
Monkeypox is a smallpox-like disease that was declared a global health emergency in July
2022. Because of this resemblance, it is not easy to distinguish a monkeypox rash from other …
2022. Because of this resemblance, it is not easy to distinguish a monkeypox rash from other …
Interpretable synthetic signals for explainable one-class time-series classification
This research paper introduces an innovative approach for explainable one-class time-
series classification (XOCTSC). The proposed method involves generating pseudounseen …
series classification (XOCTSC). The proposed method involves generating pseudounseen …
Lung Cancer Detection Systems Applied to Medical Images: A State-of-the-Art Survey
Lung cancer represents a significant global health challenge, transcending demographic
boundaries of age, gender, and ethnicity. Timely detection stands as a pivotal factor for …
boundaries of age, gender, and ethnicity. Timely detection stands as a pivotal factor for …
DIEANet: an attention model for histopathological image grading of lung adenocarcinoma based on dimensional information embedding
Z Wang, J Gao, M Li, E Zuo, C Chen, C Chen… - Scientific Reports, 2024 - nature.com
Efficient and rapid auxiliary diagnosis of different grades of lung adenocarcinoma is
conducive to helping doctors accelerate individualized diagnosis and treatment processes …
conducive to helping doctors accelerate individualized diagnosis and treatment processes …
ML3CNet: Non-local means-assisted automatic framework for lung cancer subtypes classification using histopathological images
Background and objective: Lung cancer (LC) has a high fatality rate that continuously affects
human lives all over the world. Early detection of LC prolongs human life and helps to …
human lives all over the world. Early detection of LC prolongs human life and helps to …