Lung Melanoma Recognition through Platelet Count Composition Using Supervised ML Technique

Blood samples are used to diagnose the health illness in the human body. Complete blood routine test is used as whole-body screening to detect illness in human body. Highly sensitive diagnosis can be detected by blood count such as by using RBC, RNA [12], WBC, DNA, platelet count or even protein biomarkers. Biopsies of liquid blood sample are effectively used nowadays even to detect diagnosis of cancer. By determining the routine indices of blood samples, lung carcinoma can be detected. Rather than using PET scan which is high in cost, Lung carcinoma can be detected by blood indices samples. Machine Learning can be used to decipher the multiple ranges of statistical data by using svm (support vector machine) technique from supervised learning framework. This technique can be used for identification purpose both in clinical research and by patients respectively. From the detailed report, physicians can aid the treatment cycle for the patient. Each patient's report is sent to their registered phone number via SMS using Sim900 with Arduino Uno sensor. The generated detailed report is sent to the registered mobile number as short messaging service. In this approach, advanced way of using blood indices to identify the lung carcinoma is been developed.