Idea - FICS

Smart Screening V 2.0

Team and Contact Details

Student Name School Degree Year Email
Aiman ZiaSINESMS/M.PhilSecond[email protected]
Syeda Rija HussainBenazir Bhutto HospitalUndergraduateFifth[email protected]
Ayesha AmirSINESMS/M.PhilSecond[email protected]
Nimra QaisarSINESMS/M.PhilSecond[email protected]

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: Smart Screening V 2.0
Slogan: Light The Night
Supervisor Name: Dr. Zamir Hussain
Supervisor Designation: Associate Professor
Supervisor School: SINES
Supervisor Department: Bioinformatics
Contact number: 0333-5249498
Email ID: [email protected]
Abstract:
    Efficient screening increases likelihood of early diagnosis & better treatment. Insufficient facilities, inexperienced human resource, excessive workload, disease complexity, and disparity in rules-based assessment increases false negative rate for Leukemia. Thus, a unique, user-friendly, cost-effective & smart support like “Smart Screening “is inevitable for better decision making.
What is the unmet need in society that your idea will fulfill ?
    Common subjective rules based assessments using a CBC report may lead to miss diagnosis. “Smart Screening” supports health care professionals for primary screening of Leukemia through a CBC report. Therefore, increases rate of early diagnosis and effective treatment.
Who needs it ? How many would benefit ?
   Pathologists and Medical specialist in both government and private sector could benefit through “Smart Screening”. Our application will benefit around 5% of the suspected leukemic patients and support to roughly 40,000 medical specialists and pathologists screening CBC reports in their daily routine
How will the solution works
    First phase is development of standardized process using AI to predict disease likelihood considering primary data of significant features of CBC reports (blending subject & professional knowledge domain). Second phase is product development with embedded database that requires input regarding features of CBC report for disease likelihood or category (Yes/No) as output. Next is pilot deployment for testing/validation, likely in ASAB diagnostic Lab, NUST, followed by product launching & business
Who are your competitors ? How is your solution different
    Our tech solution is unique & adaptive in terms of using local/primary data to train AI algorithms, a justifiable selection of features & a user-friendly interface. Despite the existence of informative & preventive apps like “CLLmanager”, “ALLXplained”, there is no such complete solution in market
Status: new
Entry Date & Time: 2022-12-15 (1727)