Machine learning techniques are important when generating results for accurate predictions and preventing future occurence of unwanted events.
Medical diagnosis is a serious affair. More accurate detection of a life threatening disease like cancer goes a long way in saving lives. Breast cancer prognosis has always been considered a critical area of investigation in the healthcare and medical sector.
To diagnose medical concerns various visualization techniques and models can be built for more accurate assessment of a life-threatening condition like cancer which can save a lot of lives.
Learn to build prediction models using machine learning techniques to help improve your diagnosis.
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Breast cancer prognosis has always been considered a critical area of investigation in the healthcare and medical sector, thus it is necessary to determine dependent and independent indicators.
The primary obstacle to identification is recognizing whether a tumor is aggressive (cancerous) or harmless (non-cancerous).
It is indeed extremely important to have a platform that supports early identification and prevention, hence increasing breast cancer survival rates.
Firstly, the data is summarized and visually represented to determine correlation among different indicators like tumor size, thickness etc.
VIF analysis was also done to reveal various trends and independent indicators whose presence has a significant impact of the target variable.
Classification model was built using Support Vector Machine technique.
The case can be utilized by the healthcare department to develop a predictive model.
The model can be used to predict whether the patient will receive a positive breast cancer diagnosis based on a variety of tumor characteristics.
Sophisticated models provide accurate results which can save lives.
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Learn new skills that will boost your career by enrolling in courses across data analytics, data science, ML and AI. These courses will utilize readings, videos, quizzes, data cases, and even coding exercises to teach you skills and concepts in a way that will solidify your new knowledge for hands-on application.
With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
Complete assessments and track your progress in real-time to benchmark your proficiency in relation to key functional areas. As you progress through your courses, our patented platform will utilize ML and AI to record and analyze your inputs and output to provide active feedback and recommendations that will help you learn more effectively than the standard Letter Grade system used today.
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Difficulty: Intermediate
Duration: Approximately 2 hours
