Multidisciplinary Comprehensive Effective Tracker (MCET)

Bring a smile to an autistic child by creating a system that will ensure that the children get methodical care, screening and follow ups

Problem-Statement:

A system to provide multi-disciplinary approach for intervention in Autism spectrum disorder. Currently, there is no digitalized way to track the progress of an autistic child across various disciplines.

Solution-Statement:

Develop a system where the treatment can be planned, tracked and analyzed in a systematic manner. We intend to build analytics around the past data to be able to propose a treatment plan, and corrective measures that the team of doctors/ therapists ought to take to effectively treat the condition of the autistic patient.

Team:

1) Vijaya Krishna C S
2) Nishan K A
3) Hemanth Garlapati
4) Vinoth G
5) Naveen Kumar K

WHAT MCET DELIVERS:

MCET is a comprehensive Autism Spectrum Disorder Treatment Management & Analysis System where all the data can be available with respect to every child, right from screening, assessment, health history questionnaire, interventions by various professionals including doctors, therapist and educators, follow ups and testimonials. Using the available data, system shows comprehensive graphs, data mined images, analyse frequent parameters in autism and predicts which solution works best.

HOW MCET WAS ENGINEERED:

We built the system with as a streamlined process flow model where a case is generated on a new on-boarded child and it goes through different stages for treatment, assessment and closure. We have provided the below capabilities
1) Ability for a parent to request for a call on problem identification.
2) Request call gets converted to a case if the decision is taken to on-board the child for treatment.
3) Initial assessment can be performed capturing extensive child and parental medical history profiles. Treatment plan is captured as part of the initial assessment.
4) Case transitions to the treatment stage after initial assessment. The therapists or concerned doctors from respective disciplines could track the child response and capture it as a feedback.
5) Ability for the parents to monitor and also add continuous feedback during the course of treatment.
6) Extensive reporting module to display visually various statistics at golbal level and also at a specific case level (case level reports are WIP)
7) Data Mining to dig through past case notes and retrieve the most commonly used words/therapies for similar problems and display as a tag cloud.

TECHNOLOGIES USED:

# Java, Struts for MVC framework
# Hibernate as ORM tool
# Bootstrap for UI/UX
# JavaScript, jQuery for Front-end
# D3.js, C3.js for comprehensive visual reporting
# R for Data Mining & Analytics with future scope for Machine Learning on current model.