Machine Learning and Deep Learning for Early Detection of Genetic Mutations in Various Cancers

Glioma in the pediatric population is by far the most common pediatric brain tumor and it's divided into low-grade glioma grade one and two and high gradual migration three and four low graviera accounts for around ninety per cent of the Glioma with a number which is above one thousand patients in the US per year treatment of pediatric lubricant is with surgery primarily but there are situations or places in the brain where surgery is not possible and in this context the first line treatment is chemotherapy there are various factors that affect the efficacy of chemotherapy and in particular, the molecular profile of the tumor among the molecular markers that have been identified the presence of a BRV 600 mutations is associated with a poorer response to chemotherapy and a risk of transformation we see this mutation in 15 to 20 per cent of the patient therefore a need to develop new Treatment there was initially a study of Debra phony that was conducted a few years ago that has demonstrated tolerability and efficacy in this context and due to the data in the adult population particularly in melanoma with the same mutation therapy 600 mutation the addition of traumatic was showing an improved response rate and decreased side effect therefore a logical next step was to add trametinib to dabrafenib for subsequent clinical trial in children this started in 2014 with a phase one and then a phase two study and this study shown promising results and a good safety profile.