Cancer is one of the most dangerous diseases in the whole world. Every day people are looking for ways to cure cancer. AI and its various applications are reshaping the way scientists and researchers approach cancer treatment.

Tumors are very complex diseases. It is very difficult to study the behavior of a tumor hence the treatment is much difficult. According to scientists, it is difficult to study the progression of cancer due to its uniqueness and hence its cure is difficult. But AI is changing the way Oncologists look at cancer treatment and management. Because of AI deep learning has been successfully applied to the area that was previously difficult to understand and study.

Here we talk about the major five areas where AI is making changes in Oncology.

Segmenting Tumors.

The major and immediate task before diagnosing cancer is the analysis of tumor volume. But all traditional methods like RECIST- response evaluation criteria in a solid tumor, are not effective and fast. Many modern scientists have used CNNs to segment brain tumors, liver tumor and optic tumors. This has increased the accuracy to detect tumors and segment them. The major advantage of using CNNs over semi-automated methods is that the need to customize machines manually is obviated because CNN has the ability to automatically identify features.

Diagnosing Metastases.

Skin cancer diagnosis consists of clinical screening and dermoscopic analysis followed by a biopsy and other analysis. But the recent advances in AI have created a path for less time-consuming approach. A group of researchers from Oregon State University used deep learning to extract information from the gene. This information helped them classify different types of breast cancer cells, revealing new ways for detection of breast cancer.

Applying Precision Histology.

According to researchers, histomorphology has been changed by precision histology. This is a type of deep learning for cancer and its treatment. With the introduction of AI in the healthcare industry, deep neural network (DNNs) are used which applies deep algorithms that are faster than traditional methods. DNNs have already been used to analyze the skin lesions with similar accuracy to practice dermatologists. It is believed that DNNs will soon be capable of more accurate analyses based on H&E slides. This will also lead to the new biological data pool, which will help in precision Oncology.

Tracking Tumor Development.

Deep learning has also reached to tracking tumor development and their studies. Researchers from Fraunhofer Institute for Medical Image Computing developed a deep learning model that updates itself and becomes more accurate as it reads CTs and MRIs. Also, the software allows for easy image comparison to track tumor development. With the facility to track tumor development, AI has already given a lot in the healthcare field. with everyday advancement in technology AI is more likely to be used highly in Oncology and other medical fields.

Cancer is one of the most dangerous diseases, it should be cured as fast as possible. But in the past with very less research in this field cancer treatment was almost impossible. But with the use of AI in cancer filed scientists are slowly being able to find ways of treating cancer. They are even able to track tumor development and also study phases in cancer. This has also increased the speed of different tests and treatments to be carried out. With the use of AI into cancer treatment researchers have found many ways to boost up cancer treatment. Till now AI has already contributed a lot in Oncology. But hopefully in near future due to AI technology, we might find the easiest and best way to cure cancer totally.

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