Скачать или смотреть Disease Prediction from Symptoms with Flask App using Machine Learning by Vidya Mahesh Huddar

Disease Prediction from Symptoms with Flask App using Machine Learning by Vidya Mahesh Huddar

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Disease Prediction from Symptoms with Flask App using Machine Learning Final Year Project by Vidya Mahesh Huddar

Follow the link to download the project:
https://vtupulse.com/product/disease-...

Disease Prediction from Symptoms involves use of machine learning (ML) and deep learning (DL) techniques to identify and compare medical cases based on clinical features such as symptoms, diagnoses, test results, and treatment outcomes.
This approach helps healthcare professionals find similar cases, aiding in diagnosis, treatment recommendations, and patient management.

Data Collection:
Medical records, including structured (e.g., lab results) and unstructured data (e.g., clinical notes).

Data Preprocessing:
Cleaning, normalizing, and encoding data into a machine-readable format.

Feature Extraction:
Extracting relevant features like patient demographics, vital signs, lab results, and clinical histories.

Similarity Measurement:
We use algorithms such as cosine similarity, Euclidean distance, or more advanced techniques like neural embeddings to measure case similarity.

Model Training:
Training ML models using bidirectional LSTM to learn complex patterns from labeled or unlabeled patient data.

Evaluation & Deployment:
Evaluating model performance using metrics like precision, recall, and F1-score, then deploying flask app in a healthcare application.

The following concepts are discussed:
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