Data-Source: https://www.kaggle.com/datasets/dhivyeshrk/diseases-and-symptoms-dataset

DESCRIPTION

Unique_Symptoms: 378

Preview: 'anxiety and nervousness', 'depression', 'shortness of breath', 'depressive or psychotic symptoms', 'sharp chest pain', 'dizziness', 'insomnia', 'abnormal involuntary movements', 'chest tightness', 'palpitations', ... 'stuttering or stammering', 'problems with orgasm', 'nose deformity', 'lump over jaw', 'sore in nose', 'hip weakness', 'back swelling', 'ankle stiffness or tightness', 'ankle weakness', 'neck weakness'

Unique Diseases: 773

Preview: 'panic disorder', 'vocal cord polyp', 'turner syndrome', 'cryptorchidism', 'poisoning due to ethylene glycol', 'atrophic vaginitis', 'fracture of the hand', 'cellulitis or abscess of mouth', 'eye alignment disorder', 'headache after lumbar puncture', 'pyloric stenosis', 'salivary gland disorder', 'osteochondrosis', ...... 'bladder obstruction', 'melanoma', 'cervical disorder', 'laryngitis', 'dyshidrosis', 'poisoning due to opioids', 'diaper rash', 'lichen planus', 'gastroduodenal ulcer', 'inguinal hernia', 'eczema', 'asperger syndrome', 'mucositis', 'paronychia', 'open wound of the jaw', 'white blood cell disease', 'kaposi sarcoma', 'spondylolisthesis', 'pseudotumor cerebri', 'conjunctivitis due to virus', 'open wound of the nose'

Total Samples: ~246000

Features

Data-Preprocessing Using Pandas,Numpy,Scikit-learn,mlxtend

Exploratory Data-analysis and visualizations for each unique disease.

DataTransformation using OnehotEncoder and TransactionEncoder for Encoding Categorical Features

FPgrowth and apriori for association rule-mining

Feature extraction using TfidfVectorizer on precautions

Severity mapping

Evaluation metrics confidence,support and jaccard similarity index

Tech Stack

Python 3.x

Pandas,Numpy

Plotly,matplotlib,seaborn

Scikit-learn,mlxtend

Streamlit,jupyter lab

Demonstrations