The document discusses using machine learning models to help with early stage cancer prediction. The general objective is to improve cancer diagnosis, treatment, and outcomes. Specifically, the models could assist doctors in early detection and diagnosis of cancer, help healthcare professionals make screening and treatment decisions, and personalize cancer treatment for individual patients based on their genomic and clinical profiles. The target audiences are healthcare professionals, researchers, and patients, while domain experts would be oncology researchers and business process experts would be healthcare IT professionals and project managers. Data sources could include hospitals, online datasets, and patient data.

1. P R E S E N T E D B Y
M E H W I S H M E H M O O D
Early Stage Cancer Prediction
Using ML Model

2. General Objective
 The general objective of cancer prediction using ML
is to improve cancer diagnosis, treatment, and
patient outcomes.

3. Specific Objective
 To assist doctor in the early detection and diagnosis
of cancer
 It can help healthcare professionals make informed
decisions about screening, diagnosis, and treatment.
 It can also be used to personalize cancer treatment
by predicting the most effective therapies for
individual patients based on their specific genomic
and clinical characteristics.

4. Target Audience
 Healthcare professionals
 Researchers
 Patients.

5. Domain Expert
 Researcher with expertise in oncology and cancer
diagnosis. This may include oncologists, radiologists,
pathologists, or other healthcare professionals with
specialized knowledge of cancer detection and
treatment.

6. Business process Expert
 healthcare IT professionals
 project managers

7. Data Source
 Hospital
 Online data source (Kaggle etc.)
 Patient data