HYBRID SELECTION FRAMEWORK FOR CLASS BALANCING APPROACHES BASED ON INTEGRATED CNN AND DECISION MAKING TECHNIQUES FOR LUNG CANCER DIAGNOSIS
Lung cancer is the fastest-growing and most dangerous type of cancer worldwide. It ranks first among cancer diseases in the number of deaths, and diagnosing it at late stages makes treatment more difficult. Artificial intelligence has played an essential role in the medical field in general, and ear...
保存先:
主要な著者: | Jassim M.M., Jaber M.M. |
---|---|
その他の著者: | 57843900500 |
フォーマット: | 論文 |
出版事項: |
Technology Center
2023
|
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
類似資料
-
Recent advances in the diagnosis and treatment of lung cancer
著者:: Liam, C.K., 等
出版事項: (2001) -
Lung cancer medical images classification using hybrid
CNN-SVM
著者:: Abdulrazak Yahya, Saleh, 等
出版事項: (2021) -
The diagnosis of lung cancer in the era of interventional pulmonology
著者:: Liam, C-K, 等
出版事項: (2021) -
Noise removal methodologies for lung cancer diagnosis
著者:: Nur Fatin Razlieya, Mohd Razali
出版事項: (2019) -
Developing lung cancer post-diagnosis system using pervasive
data analytic framework
著者:: Pethuraj, Mohamed Shakeel, 等
出版事項: (2023)