AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
제공자:


이 강좌에 대하여
You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.
배울 내용
Walk through examples of prognostic tasks
Apply tree-based models to estimate patient survival rates
Navigate practical challenges in medicine like missing data
귀하가 습득할 기술
- Deep Learning
- Machine Learning
- time-to-event modeling
- Random Forest
- model tuning
You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.
제공자:
강의 계획표 - 이 강좌에서 배울 내용
Linear Prognostic Models
Prognosis with Tree-based Models
Survival Models and Time
Build a Risk Model Using Linear and Tree-based Models
검토
- 5 stars78.59%
- 4 stars16.02%
- 3 stars3.17%
- 2 stars1.51%
- 1 star0.69%
AI FOR MEDICAL PROGNOSIS 의 최상위 리뷰
This course was great and more challenging that I have expected. More focus on statistics and survival data which is important for prognosis. Course has a good flow and valuable content.
Really enjoyed the flow of the course, application usages of theory was too good. Looking forward for such more courses
This course enabled me to apply machine learning for prognosis related scenario & learn multiple risk assessment related scenario.
the coding assignments were not that hard sadly, but the knowledge about techniques and methods and formulas to interpret the prognosis is very helpful
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