Topic Editors
Artificial Intelligence in Cancer Pathology and Prognosis
Topic Information
Dear Colleague,
Artificial Intelligence (AI) has transformed the landscape of cancer pathology and prognosis, presenting unparalleled opportunities for early detection, precise diagnosis, and tailored treatment strategies. This topic delves into the latest advancements in AI technologies, encompassing machine learning algorithms, deep learning models, and computer vision techniques, applied across various domains of cancer pathology. From the analysis of histopathological images to the identification of biomarkers and the prediction of patient outcomes, AI-driven approaches have exhibited remarkable efficacy in enhancing the accuracy and efficiency of both cancer diagnosis and prognosis. This topic elucidates key research findings, addresses prevailing challenges, and outlines future directions for leveraging AI to augment cancer care and management, ultimately resulting in improved patient outcomes and advancements in precision oncology. All papers from related journals are welcome for peer review.
Dr. Hamid Khayyam
Prof. Dr. Ali Hekmatnia
Dr. Rahele Kafieh
Dr. Ali Jamali
Topic Editors
Keywords
- AI
- machine learning
- cancer pathology
- prognosis
- machine learning
- deep learning
- computer vision
- precision oncology
- histopathological images
- biomarkers
- patient outcomes
Participating Journals
Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
---|---|---|---|---|---|---|
Cancers
|
4.5 | 8.0 | 2009 | 16.3 Days | CHF 2900 | Submit |
Current Oncology
|
2.8 | 3.3 | 1994 | 17.6 Days | CHF 2200 | Submit |
Diagnostics
|
3.0 | 4.7 | 2011 | 20.5 Days | CHF 2600 | Submit |
Diseases
|
2.9 | 0.8 | 2013 | 18.9 Days | CHF 1800 | Submit |
Onco
|
- | - | 2021 | 19 Days | CHF 1000 | Submit |
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