M.A.N.I.A.C.S |

Team member:

Vikash kumar

Shudhanshu shoritya

Vedant arora

Arpita kumari

Our AI chatbot is an initiative through which we want to build a women health platform, which track women specific health issues and help raise awareness for its treatment and management. With a lot of fear of the stigma associated with reproductive health services, women often avoid making use of such services. This stigma imposes a great deal of mental stress, fear, and depression on patients and causes delays in the diagnosis and treatment of their conditions. Through Our AI chatbot, we aim at solving this barrier for women to connect with doctor and try to reduce the errors and hassle in the diagnosis of the ailments.

Features

*Intuitive AI-based Chatbot capable to interact in any language

 It track the user’s periods regularly, send them reminders and also have a feature to inform the user’s parents/guardians if complications requiring immediate attention arise

Predict PCOS using AI in a person on the basis of their lifestyle and history. Tracking of previous Medical History Menstrual Cycle Tracker Booking Lab/Appointment Medical consultation from expert 24/7.

Technology Stack

Artificial Intelligence & Web Technology

• Machine Learning

  • Python - Sklearn, Keras, Tensorflow etc. for the ML Model(s)
  • Django REST Framework (for Model Endpoints)

• Frontend

  • HTML
  • CSS
  • Bootstrap

• Backend

  • PHP
  • MySQL (Database)

• Tools

  • Microsoft Azure Machine Learning Studio for the ML Model(s)
  • Xampp
  • Git
  • Github

Sample User Credentials

• For Doctor

  • Username - doctor
  • Password - doctor

• For Patient

  • Username - patient
  • Password - patient

Instructions to Install and Setup:

• clone this repo
• Go to the directory where Xampp is installed. For eg. C:\xampp\htdocs
• Copy the project folder and paste it in the address mentioned above.
• Open PhpMyAdmin, create a database named 'detail' and import the detail.sql file from the db folder present in the repo.
• Launch any browser window and search localhost/M.A.N.I.A.C.S.

References and Citations

• https://www.researchgate.net/publication/263052166_Automatic_detection_of_invasive_ductal_carcinoma_in_whole_slide_images_with_Convolutional_Neural_Networks
• https://academic.oup.com/gigascience/article/7/6/giy065/5026175
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132001/
• https://bmcwomenshealth.biomedcentral.com/articles/10.1186/s12905-020-01149-5
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408698/