Application of Artificial Intelligence-Based Classifiers to Predict the Outcome Measures and Stone-Free Status Following Percutaneous Nephrolithotomy for Staghorn Calculi: Cross-Validation of Data and Estimation of Accuracy

Author:

Hameed B.M. Zeeshan123,Shah Milap13,Naik Nithesh34,Singh Khanuja Harneet5,Paul Rahul6,Somani Bhaskar K37

Affiliation:

1. Department of Urology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India.

2. KMC Innovation Centre, Manipal Academy of Higher Education, Manipal, Karnataka, India.

3. iTRUE (International Training and Research in Uro-oncology and Endourology) Group, Manipal, Karnataka.

4. Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India.

5. Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.

6. Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA.

7. Department of Urology, University Hospital Southampton NHS Trust, Southampton, United Kingdom.

Publisher

Mary Ann Liebert Inc

Subject

Urology

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