چکیده مقاله
Deep learning has emerged as a powerful tool in medical sciences, offering innovative solutions for cancer diagnosis, classification, and treatment response prediction This review provides an overview of the applications of deep learning in oncology, focusing on its impact on improving accuracy and efficiency in cancer related tasks The use of deep learning tools, such as convolutional neural networks CNNs and recurrent neural networks RNNs , has enabled significant advancements in medical imaging analysis These tools have shown remarkable performance in classifying cancerous lesions in various imaging modalities, including MRI, CT, and PET scans Furthermore, deep learning models have been instrumental in predicting treatment outcomes for cancer patients By analyzing patient data, including genetic information and treatment histories, these models can help clinicians personalize treatment plans and improve patient outcomes Overall, this review highlights the potential of deep learning in transforming cancer care By leveraging the power of deep learning, healthcare professionals can enhance their decision making processes and provide more effective treatments for cancer patients
کلیدواژهها
نویسندگان
Ali Abbaszade-Cheragheali
Student Research Committee, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
Fateme Abdolahi
Student Research Committee, Kashan university of medical science, Kashan, Iran
شیوه ارجاع
Abbaszade Cheragheali, Ali and Abdolahi, Fateme,1402,Deep learning for cancer classification, diagnosis, and treatment response prediction,16th International Conference on Health, Treatment and Health Promotion
ارائهشده در
مجموعه مقالات شانزدهمین کنفرانس بین المللی بهداشت، درمان و ارتقای سلامت27 بهمن 1402