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    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Health Informatics

    Indian Institute of Health Management Research, Jaipur
    Duration
    4 Years
    Health Informatics UG OFFLINE

    Duration

    4 Years

    Health Informatics

    Indian Institute of Health Management Research, Jaipur
    Duration
    Apply

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Health Informatics
    UG
    OFFLINE

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    120

    ApplyCollege

    Seats

    120

    Students

    120

    Curriculum

    Course Structure Overview

    The B.Tech in Health Informatics at Iihmr University Jaipur is structured over eight semesters, with a balanced blend of core engineering subjects, science electives, departmental electives, and hands-on laboratory sessions. Each semester carries a specific credit load designed to ensure a progressive learning curve.

    SemesterCourse CodeFull Course TitleCredit Structure (L-T-P-C)Prerequisite
    1CS101Introduction to Programming3-0-2-4-
    1MATH101Calculus and Linear Algebra3-0-2-4-
    1PHYS101Physics for Engineers3-0-2-4-
    1CHEM101Chemistry for Engineering3-0-2-4-
    1BIO101Introduction to Biology3-0-2-4-
    1ENGL101English Communication Skills2-0-0-2-
    2CS201Data Structures and Algorithms3-0-2-4CS101
    2MATH201Probability and Statistics3-0-2-4MATH101
    2PHYS201Electromagnetism and Waves3-0-2-4PHYS101
    2BIO201Anatomy and Physiology3-0-2-4BIO101
    2HIST101History of Medicine2-0-0-2-
    3CS301Database Systems3-0-2-4CS201
    3MATH301Mathematical Modeling3-0-2-4MATH201
    3BIO301Cellular Biology3-0-2-4BIO201
    3HINF301Introduction to Health Informatics3-0-2-4-
    3ENGL201Technical Writing and Presentation2-0-0-2ENGL101
    4CS401Machine Learning3-0-2-4CS301, MATH301
    4BIOM401Bioinformatics Fundamentals3-0-2-4BIO301
    4HINF401Health Data Analytics3-0-2-4HINF301
    4ENGL301Professional Ethics in Healthcare2-0-0-2-
    5CS501Medical Image Processing3-0-2-4CS401, BIOM401
    5HINF501Health Information Security3-0-2-4HINF401
    5BIOM501Genomics and Proteomics3-0-2-4BIOM401
    5RESE501Research Methodology3-0-2-4-
    6CS601Advanced AI for Healthcare3-0-2-4CS501, HINF501
    6HINF601Telemedicine Systems3-0-2-4HINF501
    6BIOM601Pharmacogenomics3-0-2-4BIOM501
    6ENGL401Business Communication2-0-0-2ENGL201
    7HINF701Capstone Project I3-0-2-4-
    7RESE701Advanced Research Topics3-0-2-4RESE501
    8HINF801Capstone Project II3-0-2-4-
    8RESE801Final Thesis3-0-2-4RESE701

    Advanced Departmental Electives

    The department offers a rich selection of advanced elective courses designed to cater to various interests and career paths within health informatics.

    • Medical Image Processing: This course explores techniques for analyzing, enhancing, and interpreting medical images using computational methods. Students learn about image segmentation, feature extraction, and deep learning models tailored for medical imaging tasks.
    • Health Information Security: Focuses on safeguarding sensitive health data against unauthorized access, breaches, and cyber threats. Topics include encryption standards, risk assessment frameworks, and compliance with regulations like HIPAA and GDPR.
    • Genomics and Proteomics: Delves into the analysis of genetic and protein structures to understand disease mechanisms and develop personalized treatment plans. Students gain hands-on experience with tools used in genomic data analysis.
    • Telemedicine Systems: Examines the design and implementation of remote healthcare delivery systems, including mobile health apps, wearable sensors, and virtual consultation platforms.
    • AI for Drug Discovery: Covers how artificial intelligence is revolutionizing pharmaceutical research by accelerating compound identification, predicting drug interactions, and optimizing clinical trial designs.
    • Digital Therapeutics: Explores the development of software-based interventions that can treat medical conditions without traditional medications, focusing on behavior change, symptom monitoring, and adherence improvement.
    • Public Health Data Analytics: Teaches students how to collect, analyze, and interpret large-scale public health datasets to inform policy decisions and track epidemiological trends.
    • Healthcare Policy & Management: Provides insights into the economic, legal, and administrative aspects of healthcare systems, preparing students for leadership roles in health organizations.
    • Biostatistics for Clinical Research: Offers advanced statistical methods applied to clinical trials and observational studies, emphasizing data interpretation and hypothesis testing in healthcare settings.
    • Clinical Decision Support Systems: Introduces students to the design and evaluation of systems that assist clinicians in making informed decisions based on patient data and evidence-based guidelines.

    Project-Based Learning Philosophy

    Project-based learning is central to the program's philosophy, emphasizing experiential education and practical skill development. Mini-projects are introduced starting from the second year, allowing students to apply theoretical concepts in real-world scenarios.

    Mini-projects typically last 6-8 weeks and involve small teams of 3-5 students working under faculty supervision. These projects are evaluated based on criteria such as innovation, technical feasibility, documentation quality, and presentation skills.

    The final-year capstone project is a comprehensive endeavor that spans the entire semester. Students select their own research topics or propose innovative solutions to existing problems in healthcare delivery. They work closely with faculty mentors and industry advisors to refine their ideas and develop prototypes or models.

    Each student selects their project based on their interests, career goals, and available resources. Faculty mentors are assigned according to expertise alignment, ensuring optimal guidance throughout the process. Projects are often submitted for publication or patent consideration, providing students with tangible achievements that enhance their professional profiles.