تقرير
AI and Pathology: Steering Treatment and Predicting Outcomes
| العنوان: | AI and Pathology: Steering Treatment and Predicting Outcomes |
|---|---|
| المؤلفون: | Gupta, Rajarsi, Kaczmarzyk, Jakub, Kobayashi, Soma, Kurc, Tahsin, Saltz, Joel |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science Quantitative Biology |
| مصطلحات موضوعية: | Computer Science - Artificial Intelligence, Quantitative Biology - Quantitative Methods, Quantitative Biology - Tissues and Organs |
| الوصف: | The combination of data analysis methods, increasing computing capacity, and improved sensors enable quantitative granular, multi-scale, cell-based analyses. We describe the rich set of application challenges related to tissue interpretation and survey AI methods currently used to address these challenges. We focus on a particular class of targeted human tissue analysis - histopathology - aimed at quantitative characterization of disease state, patient outcome prediction and treatment steering. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2206.07573 |
| رقم الأكسشن: | edsarx.2206.07573 |
| قاعدة البيانات: | arXiv |
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