Page 162 - FULL REPORT 30012024

Montazeri, M., Montazeri, M., Bahaadinbeigy, K., Montazeri, M., & Afraz, A. (2022).

Application of machine learning methods in predicting schizophrenia and

bipolar disorders: A systematic review. Health Science Reports, 6(1).
https://doi.org/10.1002/hsr2.962

Mujumdar, A., & Vaidehi, V. (2019). Diabetes Prediction using Machine Learning

Algorithms. Procedia Computer Science, 165, 292–299.

https://doi.org/10.1016/j.procs.2020.01.047

Nawata, K. (2020). Risk Factors Affecting Ischemic Stroke: A Potential Side Effect of
Antihypertensive Drugs. https://www.semanticscholar.org/paper/Risk-

Factors-Affecting-Ischemic-Stroke%3A-A-Potential-

Nawata/8bf12426bd09a73707d73e634a442bb1b47b6e80

Nagarajan, K. (2023). Study of Parameters Affecting Web-Shear Capacity of Multiple
Deep Hollow Core Slab System through Finite Element Analysis.

https://www.semanticscholar.org/paper/Study-of-Parameters-Affecting-Web-
Shear-Capacity-of-Nagarajan-

Thenmozhi/76d704eea11d5242463dd5fe5ae06c2033c16540

Pal, R. (2020). A Study on Credit Scoring Models with different Feature Selection and

Machine Learning Approaches. https://www.semanticscholar.org/paper/A-
Study-on-Credit-Scoring-Models-with-different-and-Pal-

Kapali/4e06a1d72b17c9d20ab315e305066391839e9acd

Pappadà, R. (2022). Discrimination in machine learning algorithms. arXiv.org.

https://arxiv.org/abs/2207.00108

145