October 2026
M	T	W	T	F	S	S
	1	2	3	4
5	6	7	8	9	10	11
12	13	14	15	16	17	18
19	20	21	22	23	24	25
26	27	28	29	30	31

Sohanur Rohanman Sohan: Explainable AI for Anemia Prediction Using Machine Learning

Sohanur Rohanman Sohan/LinkedIn

Oct 7, 2026, 03:58

Sohanur Rohanman Sohan: Explainable AI for Anemia Prediction Using Machine Learning

Sohanur Rohanman Sohan, Junior Executive (BOE & IT) at Star News, shared a post on LinkedIn:

“Machine Learning Project Explainable AI for Anemia Prediction

I’m excited to share my recent Machine Learning project:

‘Explainable AI Based Anemia Prediction through Machine Learning’

The objective of this project was to develop a machine learning approach for predicting different anemia and related hematological conditions using CBC (Complete Blood Count) parameters.

Project Overview

1,281 patient records
14 CBC related features
9 diagnostic classes
Data preprocessing & EDA
Multiple classification models
Model evaluation using accuracy, classification reports, and confusion matrices
Exploration of SHAP-based Explainable AI

Models Explored

Logistic Regression, Decision Tree, Random Forest, XG Boost, KNN, SVM, and Stacking Classifier.

Best observed accuracy: 99.03 percent

Tools and Technologies:

Python, Pandas, NumPy, Scikit learn, XG Boost, SHAP, Matplotlib, Seaborn

Through this project, I strengthened my practical knowledge of Machine Learning, Python, Data Analysis, Model Evaluation, and Explainable AI while working on a healthcare focused problem.

This project is intended for academic and research purposes and is not a clinical diagnostic tool.

I’m excited to continue developing my skills in Machine Learning, Data Science, and Explainable AI and work on more real world problems.” Sohanur Rohanman Sohan: Explainable AI for Anemia Prediction Using Machine Learning